the spectrum and the signless laplacian spectrum of coronae abstract let g 1 g 2 be two simple connected graphs denote the corona and the edge corona of g 1 g 2 by g 1 g 2 and g 1 g 2 respectively in this paper we first introduce a new invariant the m coronal of a graph matrix m where the matrix m is associated with a graph in a prescribed way then it is used to compute the signless laplacian spectrum of g 1 g 2 and g 1 g 2 in terms of the signless laplacian spectrum of g 1 and g 2 in addition the spectrum of g 1 g 2 are also given in terms of the spectrum of g 1 and g 2 finally as an application of these results we construct many pairs of nonisomorphic signless laplacian cospectral graphs

graph zn and some graphs related to zn are determined by their spectrum abstract it is proved that graph zn is determined by its adjacency spectrum as well as its laplacian spectrum z n 1 z n 2 z n k is determined by its adjacency spectrum where n1 n2 nk are integers at least 2 wn is not determined by its adjacency spectrum but is determined by its laplacian spectrum kzn tn are determined by their laplacian spectrum respectively where k is a positive integer

absolute risk regression for competing risks interpretation link functions and prediction in survival analysis with competing risks the transformation model allows different functions between the outcome and explanatory variables however the model s prediction accuracy and the interpretation of parameters may be sensitive to the choice of link function we review the practical implications of different link functions for regression of the absolute risk or cumulative incidence of an event specifically we consider models in which the regression coefficients have the following interpretation the probability of dying from cause d during the next t years changes with a factor exp for a one unit change of the corresponding predictor variable given fixed values for the other predictor variables the models have a direct interpretation for the predictive ability of the risk factors we propose some tools to justify the models in comparison with traditional approaches that combine a series of cause specific cox regression models or use the fine gray model we illustrate the methods with the use of bone marrow transplant data

two laplacians for the distance matrix of a graph abstract we introduce a laplacian and a signless laplacian for the distance matrix of a connected graph called the distance laplacian and distance signless laplacian respectively we show the equivalence between the distance signless laplacian distance laplacian and the distance spectra for the class of transmission regular graphs there is also an equivalence between the laplacian spectrum and the distance laplacian spectrum of any connected graph of diameter 2 similarities between n as a distance laplacian eigenvalue and the algebraic connectivity are established

cause specific cumulative incidence estimation and the fine and gray model under both left truncation and right censoring summary the standard estimator for the cause specific cumulative incidence function in a competing risks setting with left truncated and or right censored data can be written in two alternative forms one is a weighted empirical cumulative distribution function and the other a product limit estimator this equivalence suggests an alternative view of the analysis of time to event data with left truncation and right censoring individuals who are still at risk or experienced an earlier competing event receive weights from the censoring and truncation mechanisms as a consequence inference on the cumulative scale can be performed using weighted versions of standard procedures this holds for estimation of the cause specific cumulative incidence function as well as for estimation of the regression parameters in the fine and gray proportional subdistribution hazards model we show that with the appropriate filtration a martingale property holds that allows deriving asymptotic results for the proportional subdistribution hazards model in the same way as for the standard cox proportional hazards model estimation of the cause specific cumulative incidence function and regression on the subdistribution hazard can be performed using standard software for survival analysis if the software allows for inclusion of time dependent weights we show the implementation in the r statistical package the proportional subdistribution hazards model is used to investigate the effect of calendar period as a deterministic external time varying covariate which can be seen as a special case of left truncation on aids related and non aids related cumulative mortality

network identifiability from intrinsic noise this paper considers the problem of inferring an unknown network of dynamical systems driven by unknown intrinsic noise inputs equivalently we seek to identify direct causal dependencies among manifest variables only from observations of these variables for linear time invariant systems of minimal order we characterise under what conditions this problem is well posed we first show that if the transfer matrix from the inputs to manifest states is minimum phase this problem has a unique solution irrespective of the network topology this is equivalent to there being only one valid spectral factor up to a choice of signs of the inputs of the output spectral density if the assumption of phase minimality is relaxed we show that the problem is characterised by a single algebraic riccati equation are of dimension determined by the number of latent states the number of solutions to this are is an upper bound on the number of solutions for the network we give necessary and sufficient conditions for any two dynamical networks to have equal output spectral density which can be used to construct all equivalent networks extensive simulations quantify the number of solutions for a range of problem sizes for a slightly simpler case we also provide an algorithm to construct all equivalent networks from the output spectral density

on the reduced signless laplacian spectrum of a degree maximal graph abstract for a simple graph g the signless laplacian of g is the matrix a g d g where a g is the adjacency matrix and d g is the diagonal matrix of vertex degrees of g the reduced signless laplacian of g is the matrix g b g where b g is the reduced adjacency matrix of g and g is the diagonal matrix whose diagonal entries are the common degrees for vertices belonging to the same neighborhood equivalence class of g a graph is said to be degree maximal if it is connected and its degree sequence is not majorized by the degree sequence of any other connected graph for a maximal graph we obtain a formula for the characteristic polynomial of its reduced signless laplacian and use the formula to derive a localization result for its reduced signless laplacian eigenvalues and to compare the signless laplacian spectral radii of two well known maximal graphs we also obtain a necessary condition for a maximal graph to have maximal signless laplacian spectral radius among all connected graphs with given numbers of vertices and edges

a class of k sample tests for comparing the cumulative incidence of a competing risk in this paper for right censored competing risks data a class of tests developed for comparing the cumulative incidence of a particular type of failure among different groups the tests are based on comparing weighted averages of the hazards of the subdistribution for the failure type of interest asymptotic results are derived by expressing the statistics in terms of counting processes and using martingale central limit theory it is proposed that weight functions very similar to those for the g p tests from ordinary survival analysis be used simulation results indicate that the asymptotic distributions provide adequate approximations in moderate sized samples

dissimilarity judgments in relation to temporal and spatial factors for the sound field in an existing hall in relation to the temporal and spatial factors of sound fields dissimilarity judgments for different source locations on a stage were performed this study is based on the model of the auditory brain system which consists of the autocorrelation and crosscorrelation mechanisms for sound signals arriving at two ears and the specialization of human cerebral hemispheres there are three temporal factors 1 1 and e extracted from the autocorrelation function and four spatial factors ll iacc iacc and w iacc from the interaural crosscorrelation function of binaural signals in addition to these temporal and spatial factors the orthogonal factors of the subjective preference for sound field t 1 and t sub were taken into account the psychological distance between sound fields of different source locations on the stage were calculated by using these temporal spatial and orthogonal factors of sound fields using these distances and their linear combination dissimilarity can be calculated results of multivariable analysis show that the calculated scale values of dissimilarity agree well with the measured scale values

regular graphs with four eigenvalues we study the connected regular graphs with four distinct eigenvalues properties and feasibility conditions of the eigenvalues are found several examples constructions and characterizations are given as well as some uniqueness and nonexistence results

nonlinear response in evaluating the subjective diffuseness of sound fields tests were conducted to determine which horizontal reflection angles are most effective in stimulating subjective diffuseness for a listener in a room paired comparison tests were carried out where subjects were asked to judge in which of two sound fields they perceived more diffuseness results show that the most effective horizontal angle depends on the frequency of the one third octave band noise as is indicated by the interaural cross correlation the remarkable finding in this investigation is that the scale value of subjective diffuseness may be formulated in terms of the 3 2 power of the magnitude of interaural cross correlation iacc and that the scale value does not vary with the frequency of the bandpass noise source

on the characterizing properties of the permanental polynomials of graphs abstract let g be a graph and a g the adjacency matrix of g the permanental polynomial of g is defined as g x per x i a g if two graphs g and h have the same permanental polynomial then g is called a per cospectral mate of h a graph g is said to be characterized by its permanental polynomial if all the per cospectral mates of g are isomorphic to g it is shown that complete graphs stars regular complete bipartite graphs and odd cycles are characterized by their permanental polynomials we prove that in general the permanental polynomial cannot characterize the paths and even cycles in particular for each l 1 and m 2 we can find non isomorphic per cospectral mates of p 4 l 3 and c 4 m respectively when we restrict our consideration to connected graphs both the paths and even cycles c 4 l 2 are characterized by their permanental polynomials

measurement of regional environmental noise by use of a pc based system an application to the noise near airport g marconi in bologna abstract measurements of aircraft noise were made at the airport g marconi in bologna by using a measurement system for regional environmental noise the system is based on the model of the human auditory brain system which is based on the interplay of autocorrelators and an interaural cross correlator acting on the pressure signals arriving at the ear entrances and takes into account the specialization of left and right human cerebral hemispheres see reference 8 measurements were taken through dual microphones at ear entrances of a dummy head the aircraft noise was characterized with the following physical factors calculated from the autocorrelation function acf and interaural cross correlation function iacf for binaural signals from the acf analysis 1 energy represented at the origin of delay 0 2 effective duration of the envelope of the normalized acf e 3 the delay time of the first peak 1 and 4 its amplitude 1were extracted from the iacf analysis 5 iacc 6 interaural delay time at which the iacc is defined iacc and 7 width of the iacf at the iacc wiaccwere extracted the factor 0 can be represented as the geometrical mean of the energies at both ears a noise source may be identified by these factors as timbre

acoustical properties of aircraft noise measured by temporal and spatial factors abstract acoustical properties of aircraft noise were investigated by means of temporal and spatial factors in sound fields based on the model of auditory brain system see reference 10 the model consists of the autocorrelation and crosscorrelation mechanisms for sound signals arriving at two ears and the specialization of human cerebral hemisphere there are four temporal factors extracted from the autocorrelation function acf 1 sound energy 0 2 effective duration of acf e 3 delay time of the first peak 1 and 4 its amplitude 1 from the interaural crosscorrelation function iacf three spatial factors are extracted as 1 magnitude of the interaural crosscorrelation iacc 2 interaural delay time at iacc iacc and 3 width of the maximum peak of the iacf wiacc it is found that the acoustical properties are well represented by the factors extracted from the acf and the iacf

on some forests determined by their laplacian or signless laplacian spectrum we consider the class of graphs whose each component is either a proper subgraph of some smith graphs or belongs to a precized subset of smith graphs we classify the graphs from the considered class into those which are determined or not determined by laplacian or signless laplacian spectrum

efficient estimation of semiparametric transformation models for counting processes summary a class of semiparametric transformation models is proposed to characterise the effects of possibly time varying covariates on the intensity functions of counting processes the class includes the proportional intensity model and linear transformation models as special cases nonparametric maximum likelihood estimators are developed for the regression parameters and cumulative intensity functions of these models based on censored data the estimators are shown to be consistent and asymptotically normal the limiting variances for the estimators of the regression parameters achieve the semi parametric efficient bounds and can be consistently estimated the limiting variances for the estimators of smooth functionals of the cumulative intensity function can also be consistently estimated simulation studies reveal that the proposed inference procedures perform well in practical settings two medical studies are provided

the complement of the path is determined by its spectrum abstract it is proved that a graph whose 0 1 adjacency matrix has the spectrum of p n the complement of the path on n vertices must be p n

graphs determined by polynomial invariants many polynomials have been defined associated to graphs like the characteristic matchings chromatic and tutte polynomials besides their intrinsic interest they encode useful combinatorial information about the given graph it is natural then to ask to what extent any of these polynomials determines a graph and in particular whether one can find graphs that can be uniquely determined by a given polynomial in this paper we survey known results in this area and at the same time we present some new results

weighted npmle for the subdistribution of a competing risk direct regression modeling of the subdistribution has become popular for analyzing data with multiple competing event types all general approaches so far are based on nonlikelihood based procedur

preliminary study on recommended time duration of source signals to be analyzed in relation to its effective duration of the auto correlation function abstract a workable model of human auditory brain system including the auto correlation function acf and the interaural cross correlation function iacf has been reported 1 subjective evaluations can be described by physical factors extracted from both the acf of sound source and the iacf the purpose of this study is to find a recommended integration time 2 t r by using several noise and sound sources existing in an office results show the most suitable integration interval from the viewpoints of the loudness and the pitch can be determined in relation to the effective duration e of the sound source

distance regularity and the spectrum of graphs abstract we deal with the question can one see from the spectrum of a graph whether it is distance regular or not up till now the answer has not been known when has precisely four distinct eigenvalues the diameter 3 case we show that in this case the answer is negative we also give positive answers in some special situations for instance if has the spectrum of a distance regular graph with diameter 3 and 1 then is distance regular our main tools are eigenvalue techniques for partitioned matrices

cospectral graphs gm switching and regular rational orthogonal matrices of level p abstract the gm switching invented by godsil and mckay is a powerful method to construct cospectral graphs in its simplest version the method can be roughly described as follows let a g be the adjacency matrix of a graph g on n vertices let q diag r i n 2 m be a block diagonal matrix where r 1 m j i 2 m is an orthogonal matrix of order 2m j is the all one matrix and i k denotes the identity matrix of order k if g satisfies certain conditions then q t a g q is an adjacency matrix of a graph g which is cospectral with g with cospectral complements in this paper we consider the problem of replacing the above r with another rational orthogonal matrix u of order 2p p an odd prime we characterize all graphs g admitting a gm switching corresponding to q diag u i n 2 p i e such that q t a g q is an adjacency matrix of a graph g and hence giving a counterpart of the gm switching method for generating cospectral graphs with cospectral complements which can be used to construct pairs of non isomorphic cospectral graphs that are not obtainable by the original gm switching method next we consider the problem of how to determine whether a given graph has a non trivial gm switching associated with some u a simple algebraic condition is presented which partially answers this question

constructing trees with given eigenvalues and angles abstract let eigenvalues and angles between eigensubspaces and the axes of the corresponding real vector space be given for a tree an algorithm for constructing all trees with given eigenvalues and angles is described

random line graphs and a linear law for assortativity for a fixed number n of nodes the number of links l in the line graph h n l can only appear in consecutive intervals called a band of l we prove that some consecutive integers can never represent the number of links l in h n l and they are called a bandgap of l we give the exact expressions of bands and bandgaps of l we propose a model which can randomly generate simple graphs which are line graphs of other simple graphs the essence of our model is to merge step by step a pair of nodes in cliques which we use to construct line graphs obeying necessary rules to ensure that the resulting graphs are line graphs two nodes to be merged are randomly chosen at each step if the cliques are all of the same size the assortativity of the line graphs in each step are close to 0 and the assortativity of the corresponding root graphs increases linearly from 1 to 0 with the steps of the nodal merging process if we dope the constructing elements of the line graphs the cliques of the same size with a relatively smaller number of cliques of different size the characteristics of the assortativity of the line graphs is completely altered we also generate line graphs with the cliques whose sizes follow a binomial distribution the corresponding root graphs with binomial degree distributions zero assortativity and semicircle eigenvalue distributions are equivalent to erd s renyi random graphs

spectral characterizations of graphs with small spectral radius abstract a graph is said to have a small spectral radius if it does not exceed the corresponding hoffmann limit value in the case of signless laplacian matrix the hoffmann limit value is equal to 2 4 38 with being the real root of x 3 4 x 4 here the spectral characterization of connected graphs with small signless laplacian spectral radius is considered it is shown that all connected graphs with small laplacian spectral radius are determined by their laplacian spectra and all but one of connected graphs with small signless laplacian spectral radius are determined by their signless laplacian spectra

note on the generalized spectral characterization of graphs having an isolated vertex abstract in this paper some sufficient conditions are given on a graph g under which it is proved that g x is determined by the generalized spectrum iff g is determined by the generalized spectrum where g x is the graph obtained from the graph g by adding an isolated vertex x

regression modeling of competing risks data based on pseudovalues of the cumulative incidence function typically regression models for competing risks outcomes are based on proportional hazards models for the crude hazard rates these estimates often do not agree with impressions drawn from plots of cumulative incidence functions for each level of a risk factor we present a technique which models the cumulative incidence functions directly the method is based on the pseudovalues from a jackknife statistic constructed from the cumulative incidence curve these pseudovalues are used in a generalized estimating equation to obtain estimates of model parameters we study the properties of this estimator and apply the technique to a study of the effect of alternative donors on relapse for patients given a bone marrow transplant for leukemia

on the kernel of integral circulant graphs abstract given a positive integer n every integral circulant graph on n vertices is isomorphic to some graph icg n d having vertex set z n z and edge set a b a b z n z gcd a b n d for a uniquely determined set d of positive divisors of n by virtue of its adjacency matrix one defines the spectrum of a graph g and naturally can ask to which degree the eigenvalues of g determine the graph itself with respect to integral circulant graphs little is known about this question which is related to a conjecture of so in this note we examine the role of the eigenvalue 0 and clarify the interrelation between the dimension of the kernel of icg n d and the graph itself for all prime powers n p k and for all positive integers n in case d is a multiplicative divisor set

asymptotic theory for the frailty model the frailty model is a generalization of cox s proportional hazards model which includes a random effect nielsen gill andersen and sorensen 1992 proposed an em algorithm to estimate the cumulative baseline hazard and the variance of the random effect here the asymptotic distribution of the estimators is given along with a consistent estimator of the asymptotic variance

predicting cumulative incidence probability by direct binomial regression we suggest a new simple approach for estimation and assessment of covariate effects for the cumulative incidence curve in the competing risks model we consider a semiparametric regression model where some effects may be time varying and some may be constant over time our estimator can be implemented by standard software our simulation study shows that the estimator works well and has finite sample properties comparable with the subdistribution approach we apply the method to bone marrow transplant data and estimate the cumulative incidence of death in complete remission following a bone marrow transplantation here death in complete remission and relapse are two competing events

general regression model for the subdistribution of a competing risk under left truncation and right censoring left truncation poses extra challenges for the analysis of complex time to event data we propose a general semiparametric regression model for left truncated and right censored competing risks data that is based on a novel weighted conditional likelihood function targeting the subdistribution hazard our parameter estimates are directly interpretable with regard to the cumulative incidence function we compare different weights from recent literature and develop a heuristic interpretation from a cure model perspective that is based on pseudo risk sets our approach accommodates external time dependent covariate effects on the subdistribution hazard we establish consistency and asymptotic normality of the estimators and propose a sandwich estimator of the variance in comprehensive simulation studies we demonstrate solid performance of the proposed method comparing the sandwich estimator with the inverse fisher information matrix we observe a bias for the inverse fisher information matrix and diminished coverage probabilities in settings with a higher percentage of left truncation to illustrate the practical utility of the proposed method we study its application to a large hiv vaccine efficacy trial dataset

consistency in a proportional hazards model incorporating a random effect supported in part by the north atlantic treaty organization under a grant awarded in 1990 conducted at the mathematical institute of the university of utrecht the netherlands

robust inference for univariate proportional hazards frailty regression models we consider a class of semiparametric regression models which are one parameter extensions of the cox j roy statist soc ser b 34 1972 187 220 model for right censored univariate failure times these models assume that the hazard given the covariates and a random frailty unique to each individual has the proportional hazards form multiplied by the frailty the frailty is assumed to have mean 1 within a known one parameter family of distributions inference is based on a nonparametric likelihood the behavior of the likelihood maximizer is studied under general conditions where the fitted model may be misspecified the joint estimator of the regression and frailty parameters as well as the baseline hazard is shown to be uniformly consistent for the pseudo value maximizing the asymptotic limit of the likelihood appropriately standardized the estimator converges weakly to a gaussian process when the model is correctly specified the procedure is semiparametric efficient achieving the semiparametric information bound for all parameter components it is also proved that the bootstrap gives valid inferences for all parameters even under misspecification we demonstrate analytically the importance of the robust inference in several examples in a randomized clinical trial a valid test of the treatment effect is possible when other prognostic factors and the frailty distribution are both misspecified under certain conditions on the covariates the ratios of the regression parameters are still identifiable the practical utility of the procedure is illustrated on a non hodgkin s lymphoma dataset

semiparametric analysis of transformation models with censored data summary a unified estimation procedure is proposed for the analysis of censored data using linear transformation models which include the proportional hazards model and the proportional odds model as special cases this procedure is easily implemented numerically and its validity does not rely on the assumption of independence between the covariates and the censoring variable the estimator is the same as the cox partial likelihood estimator in the case of the proportional hazards model moreover the asymptotic variance of the proposed estimator has a closed form and its variance estimator is easily obtained by plug in rules the method is illustrated by simulation and is applied to the veterans administration lung cancer data

isospectral drums in involution graphs and euclidean ti domains the widely investigated question can one hear the shape of a drum which kac posed in his published lecture kac 1966 am math mon 73 1 23 was eventually answered negatively in gordon et al 1992 invent math 110 1 22 by construction of isospectral pairs in up to present all known planar counter examples are constructed by a certain tiling method and in this communication we call such examples isospectral euclidean ti domains from counter examples of this type one can construct a pair of finite involution graphs in this communication we address the question as to how the isospectrality of the domains for the laplacian influences the cospectrality of the involution graphs

on the second largest laplacian eigenvalues of graphs the second largest laplacian eigenvalue of a graph is the second largest eigenvalue of the associated laplacian matrix in this paper we study extremal graphs for the extremal values of the second largest laplacian eigenvalue and the laplacian separator of a connected graph respectively all simple connected graphs with second largest laplacian eigenvalue at most 3 are characterized it is also shown that graphs with second largest laplacian eigenvalue at most 3 are determined by their laplacian spectrum moreover the graphs with maximum and the second maximum laplacian separators among all connected graphs are determined

the kite graph is determined by its adjacency spectrum abstract the kite graph is obtained by appending the complete graph with p vertices to a pendant vertex of the path graph with q vertices in this paper we prove that the kite graph is determined by its adjacency spectrum for all p and q

signed graphs cospectral with the path abstract a signed graph is said to be determined by its spectrum if every signed graph with the same spectrum as is switching isomorphic with here it is proved that the path p n interpreted as a signed graph is determined by its spectrum if and only if n 0 1 or 2 mod 4 unless n 8 13 14 17 29 or n 3

the running autocorrelation function of different music signals relating to preferred temporal parameters of sound fields this paper defines the minimum value of the effective duration of the running autocorrelation function of a music signal used in subjective preference testing a short duration signal which may relate to psychological present is more suitable for calculating the most preferred time delay of the single reflection than is the long time autocorrelation function this fact is found particularly when passages of japanese music are being played which include a wide range noise component at the very beginning of the signal and the so called ma ma is a stationary sound passage without any rapid movement this paper also shows that for subsequent reverberation time a flat frequency response may be in the range of preferred conditions such preferred conditions may be calculated by the minimum effective duration of the running autocorrelation function of source signals after passing through the a weighting network

a remark on the generalized spectral characterization of the disjoint union of graphs abstract a graph g is said to be determined by its generalized spectrum dgs for short if whenever is a graph such that and g are cospectral with cospectral complements then is isomorphic to g let g h be the disjoint union of graphs g and h in this paper we give a simple sufficient condition under which we show that g h is dgs if and only if both g and h are dgs in particular let h x be a singleton graph we show that if gcd a n det w g 1 and a n is square free then g x is dgs if and only if g is dgs where a n is the constant term of the characteristic polynomial of g and w g is the walk matrix of g it is noticed that in wang and xu 9 the authors gave a sufficient condition for g x to be dgs if g is dgs however they missed the condition that a n is square free in their theorem and the result obtained is incorrect we found a counterexample to their result without this condition and give a correct version of the result accordingly in this paper

asymptotic theory for the correlated gamma frailty model the frailty model is a generalization of cox s proportional hazard model where a shared unobserved quantity in the intensity induces a positive correlation among the survival times murphy showed consistency and asymptotic normality of the nonparametric maximum likelihood estimator npmle for the shared gamma frailty model without covariates in this paper we extend this result to the correlated gamma frailty model and we allow for covariates we discuss the definition of the nonparametric likelihood function in terms of a classical proof of consistency for the maximum likelihood estimator which goes back to wald our proof of the consistency for the npmle is essentially the same as the classical proof for the maximum likelihood estimator a new central limit theorem for processes of bounded variation is given furthermore we prove that a consistent estimator for the asymptotic variance of the npmle is given by the inverse of a discrete observed information matrix

spectral reconstruction of complex networks abstract in this paper we study the reconstruction of a network topology from the eigenvalues of its laplacian matrix we introduce a simple cost function and consider the tabu search combinatorial optimization method while comparing its performance when reconstructing different categories of networks random regular small world scale free and clustered from their eigenvalues we show that this combinatorial optimization method together with the information contained in the laplacian spectrum allows an exact reconstruction of small networks and leads to good approximations in the case of networks with larger orders we also show that the method can be used to generate a quasi optimal topology for a network associated to a dynamic process like in the case of metabolic or protein protein interaction networks of organisms

pitch strength of iterated rippled noise two versions of a cascade add attenuate and delay circuit were used to generate iterated rippled noise irn stimuli irn stimuli produce a repetition pitch whose pitch strength relative to the noise percept can be varied by changing the type of circuit the attenuation or the number of iterations in the circuit listeners were asked to use pitch strength to discriminate between various pairs of irn stimuli which differed in the type of network used to generate the sounds the number of iterations and the attenuation in the network a description based on an exponential function of the first peak of the autocorrelation function of irn stimuli is consistent with the results the discrimination data were well fit by a function based on the difference in the exponential functions of the first peak of the autocorrelation functions a magnitude estimation experiment indicated that pitch strength was an exponential function of the height of the first peak in the autocorrelation function these results suggest that the strength of the pitch of irn stimuli is based on temporal processing as might be revealed by autocorrelation

constructing graphs with given spectrum and the spectral radius at most 2 abstract two graphs are cospectral if their spectra coincide the set of all graphs that are cospectral to a given graph including the graph by itself is the cospectral equivalence class of the graph we say that a graph is determined by its spectrum or that it is a ds graph if it is a unique graph having that spectrum given n reals belonging to the interval 2 2 we want to find all graphs on n vertices having these reals as the eigenvalues of the adjacency matrix such graphs are called smith graphs our search is based on solving a system of linear diophantine equations we present several results on spectral characterizations of smith graphs

crc handbook of combinatorial designs balanced incomplete block designs and t designs2 v k l designs of small orderbibds with small block sizet designs t 3steiner systemssymmetric designsresolvable and near resolvable designslatin squares mols and orthogonal arrayslatin squaresmutually orthogonal latin squares mols incomplete molsorthogonal arrays of index more than oneorthogonal arrays of strength more than twopairwise balanced designspbds and gdds the basicspbds recursive constructionspbd closurepairwise balanced designs as linear spacespbds and gdds of higher indexpbds frames and resolvabilityother combinatorial designsassociation schemesbalanced part ternary designsbalanced tournament designsbhaskar rao designscomplete mappings and sequencings of finite groupsconfigurationscostas arrayscoveringscycle systemsdifference familiesdifference matricesdifference sets abeliandifference sets nonabeliandifference triangle setsdirected designsd optimal matricesembedding partial quasigroupsequidistant permutation arraysfactorial designsfrequency squaresgeneralized quadranglesgraph decompositions and designsgraphical designshadamard matrices and designshall triple systemshowell designsmaximal sets of molsmendelsohn designsthe oberwolfach problemordered designs and perpendicular arraysorthogonal designsorthogonal main effect planspackingspartial geometriespartially balanced incomplete block designsquasigroupsquasi symmetric designs r l designsroom squaresself orthogonal latin squares sols sols with a symmetric orthogonal mate solssom sequences with zero autocorrelationskolem sequencesspherical t designsstarterstrades and defining sets t m s netstuscan squarest wise balanced designsuniformly resolvable designsvector space designsweighing matrices and conference matriceswhist tournamentsyouden designs generalizedyouden squaresapplicationscodescomputer science selected applicationsapplications of designs to cryptographyderandomizationoptimality and efficiency comparing block designsgroup testingscheduling a tournamentwinning the lotteryrelated mathematics and computational methodsfinite groups and designsnumber theory and finite fieldsgraphs and multigraphsfactorizations of graphsstrongly regular graphstwo graphsclassical geometriesprojective planes nondesarguesiancomputational methods in design theoryindex

spectral characterization of graphs with index at most 2 5 abstract a graph is said to be determined by the adjacency spectrum ds for short if there is no other nonisomorphic graph with the same spectrum all connected graphs with index at most 2 5 are known in this paper we show that with few exceptions all of these graphs are ds

e cospectral hypergraphs and some hypergraphs determined by their spectra two k uniform hypergraphs are said to be cospectral e cospectral if their adjacency tensors have the same characteristic polynomial e characteristic polynomial a k uniform hypergraph h is said to be determined by its spectrum if there is no non isomorphic k uniform hypergraph cospectral with h in this note we give a method for constructing e cospectral hypergraphs which is similar with godsil mckay switching some hypergraphs are shown to be determined by their spectra

subjective preference for sound sources located on the stage and in the orchestra pit of an opera house abstract the present study investigates whether the subjective preference theory can be applied to the sound field in an opera house paired comparison tests were conducted to obtain scale values of subjective preference as the source locations of the music on the stage and in the orchestra pit were moved listeners were asked to give their acoustical preference the acoustical factors at each listening position were obtained from the interaural cross correlation function and binaural impulse responses measured at each listening position the relationship between the scale values of subjective preference and orthogonal acoustical factors ll iacc iacc t1 for the pit source t1 for the stage tsub for the pit source and tsub for the stage source was determined by using factor analysis which shows that the preference theory is applicable total scores obtained from factor analysis and measured scale values are in good agreement

which graphs are determined by their spectrum for almost all graphs the answer to the question in the title is still unknown here we survey the cases for which the answer is known not only the adjacency matrix but also other types of matrices such as the laplacian matrix are considered

a new method for constructing graphs determined by their generalized spectrum abstract a graph g is said to be determined by its generalized spectrum dgs for short if for any graph h h and g are cospectral with cospectral complements implies that h is isomorphic to g let g be the graph obtained from g by adding a pendent edge at every vertex of g we show that g is dgs if and only if g is dgs for some graph g this gives a simple way to construct large dgs graphs from small ones explicitly in particular we show that every graph in the infinite sequence g g g is dgs for some dgs graph g

a diagnostic system measuring orthogonal factors of sound fields in a scale model of auditorium abstract based on the model of auditory brain system which consists of the autocorrelation mechanism the interaural cross correlation mechanism between both the auditory pathways and the specialization of human cerebral hemispheres y ando 1998 architectural acoustics blending sound sources sound fields and listeners new york aip press springer verlag a new diagnostic system was developed after obtaining the binaural impulse response four orthogonal factors including the spl the initial time delay gap between the direct sound and the first reflection the subsequent reverberation time and the iacc can be analyzed for the calculation of the scale values of both global and individual subjective preferences in addition two more factors extracted from the interaural cross correlation function iacc and wiacc can be figured out also the sound energy 0 the effective duration e and fine structures of autocorrelation function of sound signals including the magnitude of first maximum 1 and its delay time 1 can be analyzed as an example of the measurement effects of reflectors array above the stage in a 1 10 scale model of auditorium at each seat are discussed here

diagnostic system based on the human auditory brain model for measuring environmental noise an application to railway noise abstract measurements of railway noise were conducted by use of a diagnostic system of regional environmental noise the system is based on the model of the human auditory brain system the model consists of the interplay of autocorrelators and an interaural crosscorrelator acting on the pressure signals arriving at the ear entrances and takes into account the specialization of left and right human cerebral hemispheres different kinds of railway noise were measured through binaural microphones of a dummy head to characterize the railway noise physical factors extracted from the autocorrelation functions acf and interaural crosscorrelation function iacf of binaural signals were used the factors extracted from acf were 1 energy represented at the origin of the delay 0 2 effective duration of the envelope of the normalized acf e 3 the delay time of the first peak 1 and 4 its amplitude o 1 the factors extracted from iacf were 5 iacc 6 interaural delay time at which the iacc is defined iacc and 7 width of the iacf at the iacc w iacc the factor 0 can be represented as a geometrical mean of energies at both ears as listening level ll

geometrical parameter combinations that correlate with early interaural cross correlation coefficients in a performance hall the previous binaural data of the authors measured inside two multi purpose performance halls are re analyzed using regression in this study it is done in an attempt to establish a framework that can improve the prediction of early interaural cross correlation coefficients iaccs but with as little measurement effort and parameters as possible the results show that regression models consist of linear combinations of polynomials of geometrical parameters when used together with the measurement schemes suggested previously by the authors are sufficient for predicting the iaccs to within engineering tolerance the predictions are better than those obtained previously by the neural network approach of the authors the relative importance of the geometrical parameters in the prediction of iaccs is also investigated

a study of graph spectra for comparing graphs and trees the spectrum of a graph has been widely used in graph theory to characterise the properties of a graph and extract information from its structure it has also been employed as a graph representation for pattern matching since it is invariant to the labelling of the graph there are however a number of potential drawbacks in using the spectrum as a representation of a graph firstly more than one graph may share the same spectrum it is well known for example that very few trees can be uniquely specified by their spectrum secondly the spectrum may change dramatically with a small change structure there are a wide variety of graph matrix representations from which the spectrum can be extracted among these are the adjacency matrix combinatorial laplacian normalised laplacian and unsigned laplacian spectra can also be derived from the heat kernel matrix and path length distribution matrix the choice of matrix representation clearly has a large effect on the suitability of spectrum in a number of pattern recognition tasks in this paper we investigate the performance of the spectra as a graph representation in a variety of situations firstly we investigate the cospectrality of the various matrix representations over large graph and tree sets extending the work of previous authors we then show that the euclidean distance between spectra tracks the edit distance between graphs over a wide range of edit costs and we analyse the accuracy of this relationship we then use the spectra to both cluster and classify the graphs and demonstrate the effect of the graph matrix formulation on error rates these results are produced using both synthetic graphs and trees and graphs derived from shape and image data

an excluding algorithm for testing whether a family of graphs are determined by their generalized spectra what kinds of graphs are determined by their spectra ds for short is a difficult problem in spectral graph theory in w wang c x xu a sufficient condition for a family of graphs being determined by their generalized spectra european j combin in press the authors give a sufficient condition for a family of graphs being ds with respect to their generalized spectra however there are many graphs in this family which do not satisfy the condition to investigate the ds property of graphs in such a situation an excluding algorithm is presented in this paper which is proved to be simple and effective as illustrated by some numerical examples