effectiveness of a loudness model for time varying sounds in equating the loudness of sentences subjected to different forms of signal processing a model for the loudness of time varying sounds glasberg and moore 2012 j audio eng soc 50 331 342 was assessed for its ability to predict the loudness of sentences that were processed to either decrease or increase their dynamic fluctuations in a paired comparison task subjects compared the loudness of unprocessed and processed sentences that had been equalized in 1 root mean square rms level 2 the peak long term loudness predicted by the model 3 the mean long term loudness predicted by the model method 2 was most effective in equating the loudness of the original and processed sentences

approximate abstractions of stochastic hybrid systems we present a constructive procedure for obtaining a finite approximate abstraction of a discrete time stochastic hybrid system the procedure consists of a partition of the state space of the system and depends on a controllable parameter given proper continuity assumptions on the model the approximation errors introduced by the abstraction procedure are explicitly computed and it is shown that they can be tuned through the parameter of the partition the abstraction is interpreted as a markov set chain we show that the enforcement of certain ergodic properties on the stochastic hybrid model implies the existence of a finite abstraction with finite error in time over the concrete model and allows introducing a finite time algorithm that computes the abstraction

approximately bisimilar symbolic models for nonlinear control systems control systems are usually modeled by differential equations describing how physical phenomena can be influenced by certain control parameters or inputs although these models are very powerful when dealing with physical phenomena they are less suited to describe software and hardware interfacing with the physical world for this reason there is a growing interest in describing control systems through symbolic models that are abstract descriptions of the continuous dynamics where each symbol corresponds to an aggregate of states in the continuous model since these symbolic models are of the same nature of the models used in computer science to describe software and hardware they provide a unified language to study problems of control in which software and hardware interact with the physical world furthermore the use of symbolic models enables one to leverage techniques from supervisory control and algorithms from game theory for controller synthesis purposes in this paper we show that every incrementally globally asymptotically stable nonlinear control system is approximately equivalent bisimilar to a symbolic model the approximation error is a design parameter in the construction of the symbolic model and can be rendered as small as desired furthermore if the state space of the control system is bounded the obtained symbolic model is finite for digital control systems and under the stronger assumption of incremental input to state stability symbolic models can be constructed through a suitable quantization of the inputs

approximation metrics for discrete and continuous systems established system relationships for discrete systems such as language inclusion simulation and bisimulation require system observations to be identical when interacting with the physical world modeled by continuous or hybrid systems exact relationships are restrictive and not robust in this paper we develop the first framework of system approximation that applies to both discrete and continuous systems by developing notions of approximate language inclusion approximate simulation and approximate bisimulation relations we define a hierarchy of approximation pseudo metrics between two systems that quantify the quality of the approximation and capture the established exact relationships as zero sections our approximation framework is compositional for a synchronous composition operator algorithms are developed for computing the proposed pseudo metrics both exactly and approximately the exact algorithms require the generalization of the fixed point algorithms for computing simulation and bisimulation relations or dually the solution of a static game whose cost is the so called branching distance between the systems approximations for the pseudo metrics can be obtained by considering lyapunov like functions called simulation and bisimulation functions we illustrate our approximation framework in reducing the complexity of safety verification problems for both deterministic and nondeterministic continuous systems

minimax regret simultaneous confidence bands for multiple regression functions abstract when a simultaneous confidence band for a multiple regression function is to be constructed one encounters the problem of choosing a band from among those available the following notion of optimality for bands is introduced suppose that the band is constructed with the purpose of giving confidence intervals for evaluations x i t of the regression function at future settings x i i 1 n of the predictor variables the settings are assumed to be unknown at the time the band is to be chosen but they are assumed to lie within a given bounded set which is referred to as the constraint set once a particular band is chosen and the predictor variable settings become known the regret for the procedure can be defined as the difference between the average width of the n intervals and the smallest possible width attainable by a band constructed using knowledge of the predictor variable settings thus the regret measures the cost of not knowing the settings when the band is chosen it is reas

modeling speech intelligibility in quiet and noise in listeners with normal and impaired hearing the speech intelligibility index sii is an often used calculation method for estimating the proportion of audible speech in noise for speech reception thresholds srts measured in normally hearing listeners using various types of stationary noise this model predicts a fairly constant speech proportion of about 0 33 necessary for dutch sentence intelligibility however when the sii model is applied for srts in quiet the estimated speech proportions are often higher and show a larger inter subject variability than found for speech in noise near normal speech levels 65 db sound pressure level spl the present model attempts to alleviate this problem by including cochlear compression it is based on a loudness model for normally hearing and hearing impaired listeners of moore and glasberg 2004 hear res 188 70 88 it estimates internal excitation levels for speech and noise and then calculates the proportion of speech above noise and threshold using similar spectral weighting as used in the sii the present model and the standard sii were used to predict sii values in quiet and in stationary noise for normally hearing and hearing impaired listeners the present model predicted siis for three listener types normal hearing noise induced and age induced hearing loss with markedly less variability than the standard sii

controlling a class of nonlinear systems on rectangles in this paper we focus on a particular class of nonlinear affine control systems of the form xdot f x bu where the drift f is a multi affine vector field i e affine in each state component the control distribution b is constant and the control u is constrained to a convex set for such a system we first derive necessary and sufficient conditions for the existence of a multiaffine feedback control law keeping the system in a rectangular invariant we then derive sufficient conditions for driving all initial states in a rectangle through a desired facet in finite time if the control constraints are polyhedral we show that all these conditions translate to checking the feasibility of systems of linear inequalities to be satisfied by the control at the vertices of the state rectangle this work is motivated by the need to construct discrete abstractions for continuous and hybrid systems in which analysis and control tasks specified in terms of reachability of sets of states can be reduced to searches on finite graphs we show the application of our results to the problem of controlling the angular velocity of an aircraft with gas jet actuators

symbolic control of stochastic systems via approximately bisimilar finite abstractions symbolic approaches for control design construct finite state abstract models that are related to the original systems then use techniques from finite state synthesis to compute controllers satisfying specifications given in a temporal logic and finally translate the synthesized schemes back as controllers for the original systems such approaches have been successfully developed and implemented for the synthesis of controllers over non probabilistic control systems in this paper we extend the technique to probabilistic control systems modelled by controlled stochastic differential equations we show that for every stochastic control system satisfying a probabilistic variant of incremental input to state stability and for every given precision e 0 a finite state transition system can be constructed which is e approximately bisimilar to the original stochastic control system moreover we provide results relating stochastic control systems to their corresponding finite state transition systems in terms of probabilistic bisimulation relations known in the literature we demonstrate the effectiveness of the construction by synthesizing controllers for stochastic control systems over rich specifications expressed in linear temporal logic our technique enables automated correct by construction controller synthesis for stochastic control systems which are common mathematical models employed in many safety critical systems subject to structured uncertainty

symbolic models for nonlinear control systems alternating approximate bisimulations symbolic models are abstract descriptions of continuous systems in which symbols represent aggregates of continuous states in the last few years there has been a growing interest in the use of symbolic models as a tool for mitigating complexity in control design in fact symbolic models enable the use of well known algorithms in the context of supervisory control and algorithmic game theory for controller synthesis since the 1990s many researchers faced the problem of identifying classes of dynamical and control systems that admit symbolic models in this paper we make further progress along this research line by focusing on control systems affected by disturbances our main contribution is to show that incrementally globally asymptotically stable nonlinear control systems with disturbances admit symbolic models

on enhancement of spectral contrast in speech for hearing impaired listeners a digital processing method is described for altering spectral contrast the difference in amplitude between spectral peaks and valleys in natural utterances speech processed with programs implementing the contrast alteration procedure was presented to listeners with moderate to severe sensorineural hearing loss the task was a three alternative b d or g stop consonant identification task for consonants at a fixed location in short nonsense utterances overall tokens with enhanced contrast showed moderate gains in percentage correct stop consonant identification when compared to unaltered tokens conversely reducing spectral contrast generally reduced percent correct stop consonant identification contrast alteration effects were inconsistent for utterances containing d the observed contrast effects also interacted with token intelligibility

symbolic models for nonlinear control systems without stability assumptions finite state models of control systems were proposed by several researchers as a convenient mechanism to synthesize controllers enforcing complex specifications most techniques for the construction of such symbolic models have two main drawbacks either they can only be applied to restrictive classes of systems or they require the exact computation of reachable sets in this paper we propose a new abstraction technique that is applicable to any nonlinear sampled data control system as long as we are only interested in its behavior in a compact set moreover the exact computation of reachable sets is not required the effectiveness of the proposed results is illustrated by synthesizing a controller to steer a vehicle

model robustness for simultaneous confidence bands abstract confidence bands for the simple linear model are examined to assess their degrees of robustness to departures from the model all calculations are made under an interval constraint on the range of interest for the predictor variable the true model is taken to be a quadratic polynomial and departure from the linear case is considered in terms of increasing magnitude of a curvature parameter proposed measures of robustness include the actual coverage probability under the true model and a measure of percentage coverage over the predictor variable axis when the band fails to cover the true quadratic model the different band functions considered include hyperbolic bands constructed from scheffd s 5 method linear segmented bands and fixed width minimax and minimax regret bands in terms of preserving coverage probability under quadratic mis specification the fixed width and linear segment bands perform best the former being preferred when the constraint interval on the predictor variable is

effect of loudness recruitment on the perception of amplitude modulation people with hearing loss of cochlear origin usually display loudness recruitment the rate of growth of loudness level with increasing sound level is greater than for a normally hearing person loudness recruitment has usually been studied with steady sounds of relatively long duration the present study examines how recruitment affects the perception of dynamically varying sounds namely amplitude modulated sinusoids the modulation rates used 4 8 16 and 32 hz were chosen to span the range of the most prominent modulations present in the envelope of speech three subjects with unilateral cochlear hearing loss were used in experiment 1 subjects were required to make loudness matches between 1 khz tones presented alternately to the two ears this was done over a wide range of sound levels experiment 2 used 1 khz carriers that were amplitude modulated the modulation was sinusoidal on a db scale the modulated tones were presented alternately to the two ears and were approximately equally loud in the two ears the modulation depth was fixed in one ear and the subject was required to adjust the modulation depth in the other ear so that the modulation depth appeared equal in the two ears this was done for a range of modulation depths and with the fixed tone presented to both the normal and the impaired ear a given modulation depth in the impaired ear was matched by a greater modulation depth in the normal ear to a first approximation the modulation matching functions were independent of modulation rate furthermore the functions could be predicted reasonably well from the loudness matching results of experiment 1 obtained with steady tones the results are consistent with the idea that loudness recruitment results from the loss of a fast acting compressive nonlinearity that operates in the normal peripheral auditory system possible implications of the results for the use of fast acting compression in hearing aids are discussed

evaluation of near end speech enhancement under equal loudness constraint for listeners with normal hearing and mild to moderate hearing loss four algorithms designed to enhance the intelligibility of speech when noise is added after processing were evaluated under the constraint that the speech should have the same loudness before and after processing as determined using a loudness model the algorithms applied spectral modifications and two of them included dynamic range compression on average the methods with dynamic range compression required the least level adjustment to equate loudness for the unprocessed and processed speech subjects with normal hearing experiment 1 and mild to moderate hearing loss experiment 2 were tested using unmodified and enhanced speech presented in speech shaped noise ssn and a competing speaker cs the results showed a the algorithms with dynamic range compression yielded the largest intelligibility gains in both experiments and for both types of background b the algorithms without dynamic range compression either yielded benefit only with the ssn or yielded no consistent benefit c speech rec

comparing scheffe type to constant width confidence bounds in regression abstract conditions are given for when the scheffe type bound has smaller average width than the constant width bound when coverage probabilities are equal for bounding a multilinear regression function with intercept over one of the ellipsoidal regions of halperin and gurian 1968 the conditions depend on the size of the region relative to the design and they are shown to hold for the special case of an orthogonal design when the regressors are restricted to the boundary of the region

the loudness of sounds whose spectra differ at the two ears moore and glasberg 2007 j acoust soc am 121 1604 1612 developed a model for predicting the loudness of dichotic sounds the model gave accurate predictions of data in the literature except for an experiment of zwicker and zwicker 1991 j acoust soc am 89 756 764 in which sounds with non overlapping spectra were presented to the two ears the input signal was noise with the same intensity in each critical band bark this noise was filtered into 24 bands each 1 bark wide the bands were then grouped into wider composite bands consisting of 1 2 4 or 12 successive sub bands and each composite band was presented either to one ear or the other loudness estimates obtained using a scaling procedure decreased somewhat as the number of composite bands increased and their width decreased but the predictions of the model showed the opposite pattern this experiment was similar to that of zwicker and zwicker except that the widths of the bands were based on the erb n number scale and a loudness matching procedure was used the pattern of the results was consistent with the predictions of the model showing an increase in loudness as the number of composite bands increased and their spacing decreased

symbolic models for nonlinear control systems affected by disturbances in the last few years there has been a growing interest in the use of symbolic models for the formal verification and control design of purely continuous or hybrid systems symbolic models are abstract descriptions of continuous systems where one symbol corresponds to an aggregate of continuous states in this article we face the problem of deriving symbolic models for nonlinear control systems affected by disturbances the main contribution of this article is in proposing symbolic models that can be effectively constructed and that approximate nonlinear control systems affected by disturbances in the sense of alternating approximate bisimulation

the detailed shapes of equal loudness level contours at low frequencies high resolution equal loudness level contours elcs were measured over the frequency range 10 250 hz using 19 normal hearing subjects three levels of the 50 hz reference sound were used corresponding to the levels at 50 hz of the 30 50 and 70 phon standardized elcs given in iso 226 2003 the dynamic range of the contours generally decreased with increasing reference level and the slope was shallow between 10 and 20 hz consistent with previous studies for the lowest level the elcs were sometimes but not always smooth and on average followed the standardized 30 phon contour for frequencies above 40 hz for the two higher levels the individual elcs showed a distinct non monotonic feature in a transition region between about 40 and 100 hz where the slope could reach near zero or even positive values the pattern of the non monotonic feature was similar across levels for the subjects for whom it was observed but the pattern varied across subjects below 40 hz the slopes of the elcs increased m

on input to state stability of stochastic retarded systems with markovian switching this note develops a razumikhin type theorem on pth moment input to state stability of hybrid stochastic retarded systems also known as stochastic retarded systems with markovian switching which is an improvement of an existing result an application to hybrid stochastic delay systems verifies the effectiveness of the improved result

confidence bands for logistic regression with restricted predictor variables confidence bands are constructed for the logistic response function when there is an interval restriction on each of the predictor variables the construction involves application of a general fitting procedure using scheffe s s method described by casella and strawderman 1980 journal of the american statistical association 75 862 868 specific details are given for the case of one predictor variable along with details for a fixed width alternative to the s method bands in the one predictor case monte carlo results suggest that both bands are conservative for small sample sizes such as n 25 by n 200 the s method s coverage probabilities are seen to attain their nominal levels while the fixed width bands remain conservative the procedures are exemplified with data from a genetic toxicology experiment

symbolic models for stochastic switched systems stochastic switched systems are a relevant class of stochastic hybrid systems with probabilistic evolution over a continuous domain and control dependent discrete dynamics over a finite set of modes in the past few years several different techniques have been developed to assist in the stability analysis of stochastic switched systems however more complex and challenging objectives related to the verification of and the controller synthesis for logic specifications have not been formally investigated for this class of systems as of yet with logic specifications we mean properties expressed as formulae in linear temporal logic or as automata on infinite strings this paper addresses these complex objectives by constructively deriving approximately equivalent bisimilar symbolic models of stochastic switched systems more precisely this paper provides two different symbolic abstraction techniques one requires state space discretization but the other one does not require any space discretization which can be potentially more efficient than the first one when dealing with higher dimensional stochastic switched systems both techniques provide finite symbolic models that are approximately bisimilar to stochastic switched systems under some stability assumptions on the concrete model this allows formally synthesizing controllers switching signals that are valid for the concrete system over the finite symbolic model by means of mature automata theoretic techniques in the literature the effectiveness of the results are illustrated by synthesizing switching signals enforcing logic specifications for two case studies including temperature control of a six room building

verification of general markov decision processes by approximate similarity relations and policy refinement in this work we introduce new approximate similarity relations that are shown to be key for policy or control synthesis over general markov decision processes the models of interest are discrete time markov decision processes endowed with uncountably infinite state spaces and metric output or observation spaces the new relations underpinned by the use of metrics allow in particular for a useful trade off between deviations over probability distributions on states and distances between model outputs we show that the new probabilistic similarity relations inspired by a notion of simulation developed for finite state models can be effectively employed over general markov decision processes for verification purposes and specifically for control refinement from abstract models

effects of compression and onset offset asynchronies on the detection of one tone in the presence of another the weaker of two temporally overlapping complex tones can be easier to hear when the tones are asynchronous than when they are synchronous this study explored how the use of fast and slow five channel amplitude compression as might be used in hearing aids affected the ability to use onset and offset asynchronies to detect one signal complex tone when another masking complex tone was presented almost simultaneously a 2 1 compression ratio was used with normal hearing subjects and individual compression ratios and gains recommended by the cam2 hearing aid fitting method were used for hearing impaired subjects when the signal started before the masker there was a benefit of compression for both normal hearing and hearing impaired subjects when the signal finished after the masker there was a benefit of fast compression for the normal hearing subjects but no benefit for most of the hearing impaired subjects except when the offset asynchrony was relatively large 100 ms the benefit of compression probably occurred because the compression improved the effective signal to masker ratio hence reducing backward and forward masking this apparently outweighed potential deleterious effects of distortions in envelope shape and the introduction of partially correlated envelopes of the signal and masker

establishing convexity of polynomial lyapunov functions and their sublevel sets there has been renewed interest in the use of polynomial and homogeneous polynomial lyapunov functions for addressing stability and performance issues in systems and control theory however no condition is yet available to establish the convexity of these functions and the convexity of their sublevel sets properties that can be useful in many applications in this paper new conditions for establishing these convexity properties are proposed which can be handled through convex linear matrix inequalities optimizations by means of sum of squares relaxations

further evidence that fundamental frequency difference limens measure pitch discrimination difference limens for complex tones dlcs that differ in f0 are widely regarded as a measure of periodicity pitch discrimination however because f0 changes are inevitably accompanied by changes in the frequencies of the harmonics dlcs may actually reflect the discriminability of individual components to test this hypothesis dlcs were measured for complex tones the component frequencies of which were shifted coherently upward or downward by f 0 25 37 5 or 50 of the f0 yielding fully harmonic f 0 strongly inharmonic f 25 37 5 or odd harmonic f 50 tones if dlcs truly reflect periodicity pitch discriminability they should be larger worse for inharmonic tones than for harmonic and odd harmonic tones because inharmonic tones have a weaker pitch consistent with this prediction the results of two experiments showed a non monotonic dependence of dlcs on f with larger dlcs for f s of 25 or 37 5 than for f s of 0 or 50 of f0 these findings are consistent with

average width optimality for confidence bands in simple linear regression abstract the problem of constructing optimal confidence bands for a simple linear regression over the whole real line is considered optimality is defined as minimization of the average width of the bands weighted by a normalized function this weight function is presented as an indicator of experimental interest in the varying width of the band a comparison between the commonly seen hyperbolic bands and segmented line bands is presented

prediction of absolute thresholds and equal loudness contours using a modified loudness model the loudness model described by moore et al j audio eng soc 45 224 240 1997 forms the basis for a recent ansi standard for the calculation of the loudness of steady sounds however the model does not give accurate predictions of the absolute thresholds published in a recent iso standard here it is described how the assumed middle ear transfer function in the model can be modified to give more accurate absolute threshold predictions the modified model also gives reasonably accurate predictions of the equal loudness contours published in a recent iso standard

approximately bisimilar symbolic models for randomly switched stochastic systems in the past few years there has been a growing interest in the use of symbolic models for control systems the main reason is the possibility to leverage algorithmic techniques over symbolic models to synthesize controllers that are valid for the concrete control systems such controllers can enforce complex logical specifications that are otherwise hard if not impossible to establish on the concrete models with classical control techniques examples of such specifications include those expressible via linear temporal logic or as automata on infinite strings a relevant goal in this research line is in the identification of classes of systems that admit symbolic models in particular continuous time systems with stochastic or hybrid dynamics have been only recently considered due to their rather general and complex dynamics in this work we make progress in this direction by enlarging the class of stochastic hybrid systems admitting finite symbolic models specifically we show that randomly switched stochastic systems satisfying some incremental stability assumption admit such models

uniform confidence bands characterization and optimality abstract this paper studies optimal uniform confidence bands for functions g x 0 where 0 is an unknown parameter vector we provide a simple characterization of a general class of taut 1 uniform confidence bands allowing for both nonlinear functions and nonparametrically estimated functions specifically we show that all taut bands can be obtained from projections on confidence sets for 0 and we characterize the class of sets which yield taut bands using these results we then present a computational method for selecting an approximately optimal confidence band for a given objective function we illustrate the applicability of these results in numerical applications

equal loudness level contours for pure tones equal loudness level contours provide the foundation for theoretical and practical analyses of intensity frequency characteristics of auditory systems since 1956 equal loudness level contours based on the free field measurements of robinson and dadson br j appl phys 7 166 181 1956 have been widely accepted however in 1987 some questions about the general applicability of these contours were published h fastl and e zwicker fortschritte der akustik daga 87 pp 189 193 1987 as a result a new international effort to measure equal loudness level contours was undertaken the present paper brings together the results of 12 studies starting in the mid 1980s to arrive at a new set of contours the new contours estimated in this study are compared with four sets of classic contours taken from the available literature the contours described by fletcher and munson j acoust soc am 5 82 108 1933 exhibit some overall similarity to our proposed estimated contours in the mid frequency range up to 60 phons the contours described by robinson and dadson exhibit clear differences from the new contours these differences are most pronounced below 500 hz and the discrepancy is often as large as 14 db

reachability and control synthesis for piecewise affine hybrid systems on simplices in this paper we consider the synthesis of control laws for piecewise affine hybrid systems on simplices the construction is based on the solution to the control to facet problem at the continuous level and on dynamic programming at the discrete level the construction is given as an explicit algorithm using only linear algebra and reach set computations for automata no numerical integration is required the method is conservative in that it may fail to find a control law where one exists but one cannot hope for a sharp algorithm for control synthesis since reachability for piecewise affine hybrid systems is undecidable

approximations of stochastic hybrid systems this paper develops a notion of approximation for a class of stochastic hybrid systems that includes as special cases both jump linear stochastic systems and linear stochastic hybrid automata our approximation framework is based on the recently developed notion of the so called stochastic simulation functions these lyapunov like functions can be used to rigorously quantify the distance or error between a system and its approximate abstraction for the class of jump linear stochastic systems and linear stochastic hybrid automata we show that the computation of stochastic simulation functions can be cast as a tractable linear matrix inequality problem this enables us to compute the modeling error incurred by abstracting some of the continuous dynamics or by neglecting the influence of stochastic noise or even the influence of stochastic discrete jumps

confidence bands for polynomial regression with fixed intercepts confidence bands are considered for linear and quadratic regression when the regression equation is forced through a fixed point in the linear case it is noted that the construction of confidence bands reduces to the construction of a confidence interval on the slope parameter the corresponding bands are straight lines whose widths are independent of the size of the set over which the band is constructed the construction for the quadratic case involves more complex arguments these are developed and tables are presented for band use in both the homoscedastic and heteroscedastic settings an example is included

the reduction of the width of confidence bands in linear regression abstract when constructing a confidence band in the linear regression model there have been various efforts made to reduce the width of the band one of them is to change the shape of a confidence band another effort is to restrict the region of the independent variables this article proposes another possibility to narrow down the width of a band which is to change the curvature of the band following that a theorem is given to combine these devices numerical comparisons are carried out to see how the improvement due to the restriction of the independent variable works depending on the value of the curvature and the size of the restriction region for a couple of given band shapes the results are shown by graphs the following facts are observed an improvement by restricting the region of the independent variables without changing the curvature of the band which is my predecessors method does not bring the minimum average width we must adjust the curvature at the same time to obtain the best ban

stability analysis of deterministic and stochastic switched systems via a comparison principle and multiple lyapunov functions this paper presents a general framework for analyzing stability of nonlinear switched systems by combining the method of multiple lyapunov functions with a suitably adapted comparison principle in the context of stability in terms of two measures for deterministic switched systems this leads to a unification of representative existing results and an improvement upon the current scope of the method of multiple lyapunov functions for switched systems perturbed by white noise we develop new results which may be viewed as natural stochastic counterparts of the deterministic ones in particular we study stability of deterministic and stochastic switched systems under average dwell time switching