pinecone/core-2020-05-10-deduplication huggingface dataset:
Robust H-infinity filtering for 2-D systems with intermittent measurements

This paper is concerned with the problem of robust H∞ filtering for uncertain two-dimensional (2-D) systems with intermittent measurements. The parameter uncertainty is assumed to be of polytopic type, and the measurements transmission is assumed to be imperfect, which is modeled by a stochastic variable satisfying the Bernoulli random binary distribution. Our attention is focused on the design of an H∞ filter such that the filtering error system is stochastically stable and preserves a guaranteed H∞ performance. This problem is solved in the parameter-dependent framework, which is much less conservative than the quadratic approach. By introducing some slack matrix variables, the coupling between the positive definite matrices and the system matrices is eliminated, which greatly facilitates the filter design procedure. The corresponding results are established in terms of linear matrix inequalities, which can be easily tested by using standard numerical software. An example is provided to show the effectiveness of the proposed approac
A Fully Differential Digital CMOS Pulse UWB Generator

A new fully-digital CMOS pulse generator for impulse-radio Ultra-Wide-Band (UWB) systems is presented. First, the shape of the pulse which best fits the FCC regulation in the 3.1-5 GHz sub-band of the entire 3.1-10.6 GHz UWB bandwidth is derived and approximated using rectangular digital pulses. In particular, the number and width of pulses that approximate an ideal template is found through an ad-hoc optimization methodology. Then a fully differential digital CMOS circuit that synthesizes the pulse sequence is conceived and its functionality demonstrated through post-layout simulations. The results show a very good agreement with the FCC requirements and a low power consumptio
Wide-Dynamic-Range and High-Sensitivity Current-to-Voltage Converters

A wide dynamic range and a high sensitivity are often incompatible with each other in analog circuits, such as signal converters or amplifiers. In this paper, we present a method of developing current-to-voltage converters featuring both. It comprises two current-to-voltage conversions. One is to convert the DC component, i.e., the average level of the current input, into a voltage with a nonlinear compression. The other is to apply a ?linear? conversion to the signal component of the input current. This conversion is considered to be ?linear? as the gain is made to be almost constant if the varying signal is rippling at a given current level, and to increase if the level is changed to be lower. Hence, the gain is adaptive to the input current, i.e., getting stronger if the current signal is weaker, and vice versa. This adaptability is implemented by (a) an adaptive bias by means of the voltage converted from the DC component of the input current, and (b) the current-dependent finite drain-source resistances of MOS transistors. A low-pass current filter is used, in the proposed conversion operation, to separate the DC component of the input current from the signal one. We propose, in this paper, a basic structure of the filter and techniques to improve the filtering quality over a wide current range, also an approach to an effective reduction of the effect of the device mismatch as well. A design example of the proposed conversion is presented in this paper. The simulation results have shown its dynamic range of 5-decades and its sensitivity high enough to detect sub-nA current variations
Direction of Arrival Estimation using EM-ESPRIT with nonuniform arrays

International audienceAbstract This paper deals with the problem of the Direction Of Arrival (DOA) estimation with nonuniform linear arrays. The proposed method is based on the Expectation Maximization method where ESPRIT is used in the maximization step. The key idea is to iteratively interpolate the data to a virtual uniform linear array in order to apply ESPRIT to estimate the DOA. The iterative approach allows to improve the interpolation using the previously estimated DOA. One of this method novelties lies in its capacity of dealing with any nonuniform array geometry. This technique manifests significant performance and computational advantages over previous algorithms such as Spectral MUSIC, EM-IQML and the method based on manifold separation technique. EM-ESPRIT is shown to be more robust to additive noise. Furthermore, EM-ESPRIT fully exploits the advantages of using a nonuniform array over a uniform array: simulations show that for the same aperture and with less number of sensors, the nonuniform array presents almost identical performance as the equivalent uniform array
Distributed information consensus filters for simultaneous input and state estimation

This paper describes the distributed information filtering where a set of sensor networks are required to simultaneously estimate input and state of a linear discrete-time system from collaborative manner. Our research purpose is to develop a consensus strategy in which sensor nodes communicate within the network through a sequence of Kalman iterations and data diffusion. A novel recursive information filtering is proposed by integrating input estimation error into measurement data and weighted information matrices. On the fusing process, local system state filtering transmits estimation information using the consensus averaging algorithm, which penalizes the disagreement in a dynamic manner. A simulation example is provided to compare the performance of the distributed information filtering with optimal Gillijins–De Moor’s algorithm
Piecewise Nonlinear Approach to the Implementation of Nonlinear Current Transfer Functions

A piecewise nonlinear approach to the nonlinear circuit design has been proposed in this paper. It is to approximate a target nonlinear transfer function by a particular combination of selected nonlinear pieces. The pieces can be produced by one or more analog blocks involving nonlinear devices. This approach can be applied to design nonlinear circuits to implement various current transfer functions. By controlling the operation modes of the transistor pair in a simple current mirror, one can modulate the current transfer function in a radical or fine-tuning manner. It is thus possible for the same current mirror to generate very different nonlinear pieces in different sections of its input range. In order that the control is done automatically by the input current, or in other words, the operation of the transistors is made to be input-current-dependent in a controlled manner, a series structure of two transistors has been proposed to be incorporated in the current mirror. The dependency can be made different by placing the structure in different places of the current mirror and/or by making the two transistors complementary or not, which makes the variations of the nonlinear function. Several current mirrors have been designed. Each of them consists of a very small number of transistors and performs a defined nonlinear current transfer function. The circuits have been simulated with HSPICE to validate the functions. The successful results have been obtained and are presented in the paper
Input-output finite-time stability of discrete-time impulsive switched linear systems with state delays

Published version of an article in the journal: Circuits, Systems, and Signal Processing. Also available from the publisher at: http://dx.doi.org/10.1007/s00034-013-9610-7This paper is concerned with the problem of input-output finite-time stability (IO-FTS) for discrete impulsive switched systems with state delays. Sufficient conditions are presented for the existence of IO-FTS for such systems under the cases of certain switching, arbitrary switching, and uncertain switching. All the obtained results are formulated in a set of linear matrix inequalities (LMIs). Two numerical examples are given to illustrate the effectiveness of the proposed results
Positive L1 observer design for positive Switched systems

Published version of an article in the journal: Circuits, Systems, and Signal Processing. Also available from the publisher at: http://dx.doi.org/10.1007/s00034-013-9737-6This paper investigates the problem of L1 observer design for positive switched systems. Firstly, a new kind of positive L1 observer is proposed for positive switched linear delay-free systems with observable and unobservable subsystems. Based on the average dwell time approach, a sufficient condition is proposed to ensure the existence of the positive L1 observer. Under the condition obtained, the estimated error converges to zero exponentially, and the L1 -gain from the disturbance input to the estimated error is less than a prescribed level. Then the proposed design result is extended to positive switched systems with mixed time-varying delays, where the mixed time-varying delays are presented in the form of discrete delay and distributed delay. Finally, two numerical examples are given to demonstrate the feasibility of the obtained results
Detection of channel variations to improve channel estimation methods

“The final publication is available at Springer via http://dx.doi.org/[10.1007/s00034-014-9767-8]”[Abstract] In current digital communication systems, channel information is typically
acquired by supervised approaches that use pilot symbols included in the transmit
frames. Given that pilot symbols do not convey user data, they penalize throughput
spectral efficiency, and transmit energy consumption of the system. Unsupervised
channel estimation algorithms could be used to mitigate the aforementioned drawbacks
although they present higher computational complexity than that offered by
supervised ones. This paper proposes a simple decision method suitable for slowly
varying channels to determine whether the channel has suffered a significant variation,
which requires to estimate the matrix of the recently changed channel. Otherwise, a
previous estimate is used to recover the transmitted symbols. The main advantage of
this method is that the decision criterion is only based on information acquired during
the time frame synchronization, which is carried out at the receiver. We show that the
proposed criterion provides a considerable improvement of computational complexity
for both supervised and unsupervised methods, without incurring in a penalization in
terms of symbol error ratio. Specifically, we consider systems that make use of the popular
Alamouti code. Performance evaluation is accomplished by means of simulated
channels as well as making use of indoor wireless channels measured using a testbed
Reducing the dissipated energy in multi-standard turbo and LDPC decoders

ParallelLow-DensityParity-Checkandturbocodedecodingconsistsofiter- ative processes that rely on the exchange of messages among multiple processing ele- ments (PEs). They are characterized by complex communication patterns that require area expensive interconnect and memory management. Channel decoders based on Networks-on-Chip (NoCs) have been proposed in the literature, showing unmatched degreesofflexibility,butyieldinghighareaoccupationandpowerconsumption.While general and application-specific power reduction techniques are available to save energy, the gap with respect to dedicated decoders is still large. This paper proposes techniques that reduce and optimize the traffic on the network for NoC-based chan- nel decoders, and can be applied to any NoC architecture. The proposed techniques exploit the probabilistic nature and the processing order of the exchanged messages in the iterative decoding and define novel importance and urgency metrics. Given a target throughput, these techniques allow to consistently reduce and optimize the NoC traffic with minor or no bit error rate (BER) degradation with respect to a decoder with no traffic optimization. An already available NoC-based decoder enhanced with the proposed traffic shaping techniques leads to 13.1 % area overhead and 15.0 % power and energy reduction, while 40.2 % of power is saved on the NoC alon
Improved i-vector representation for speaker diarization

This paper proposes using a previously well-trained deep neural network (DNN) to enhance the i-vector representation used for speaker diarization. In effect, we replace the Gaussian Mixture Model (GMM) typically used to train a Universal Background Model (UBM), with a DNN that has been trained using a different large scale dataset. To train the T-matrix we use a supervised UBM obtained from the DNN using filterbank input features to calculate the posterior information, and then MFCC features to train the UBM instead of a traditional unsupervised UBM derived from single features. Next we jointly use DNN and MFCC features to calculate the zeroth and first order Baum-Welch statistics for training an extractor from which we obtain the i-vector. The system will be shown to achieve a significant improvement on the NIST 2008 speaker recognition evaluation (SRE) telephone data task compared to state-of-the-art approaches
Least squares-based iterative identification methods for linear-in-parameters systems using the decomposition technique

By extending the least squares-based iterative (LSI) method, this paper presents a decomposition-based LSI (D-LSI) algorithm for identifying linear-in-parameters systems and an interval-varying D-LSI algorithm for handling the identification problems of missing-data systems. The basic idea is to apply the hierarchical identification principle to decompose the original system into two fictitious sub-systems and then to derive new iterative algorithms to estimate the parameters of each sub-system. Compared with the LSI algorithm and the interval-varying LSI algorithm, the decomposition-based iterative algorithms have less computational load. The numerical simulation results demonstrate that the proposed algorithms work quite well
Energy-efficient 8-point DCT Approximations: Theory and Hardware
  Architectures

Due to its remarkable energy compaction properties, the discrete cosine
transform (DCT) is employed in a multitude of compression standards, such as
JPEG and H.265/HEVC. Several low-complexity integer approximations for the DCT
have been proposed for both 1-D and 2-D signal analysis. The increasing demand
for low-complexity, energy efficient methods require algorithms with even lower
computational costs. In this paper, new 8-point DCT approximations with very
low arithmetic complexity are presented. The new transforms are proposed based
on pruning state-of-the-art DCT approximations. The proposed algorithms were
assessed in terms of arithmetic complexity, energy retention capability, and
image compression performance. In addition, a metric combining performance and
computational complexity measures was proposed. Results showed good performance
and extremely low computational complexity. Introduced algorithms were mapped
into systolic-array digital architectures and physically realized as digital
prototype circuits using FPGA technology and mapped to 45nm CMOS technology.
All hardware-related metrics showed low resource consumption of the proposed
pruned approximate transforms. The best proposed transform according to the
introduced metric presents a reduction in power consumption of 21--25%.Comment: 21 pages, 7 figures, 5 table
Sparse Blind Speech Deconvolution with Dynamic Range Regularization and Indicator Function

Blind deconvolution is an ill-posed problem. To solve such a prob- lem, prior information, such as, the sparseness of the source (i.e. input) signal or channel impulse responses, is usually adopted. In speech deconvolution, the source signal is not naturally sparse. However, the direct impulse and early reflections of the impulse responses of an acoustic system can be considered as sparse. In this paper, we exploit the channel sparsity and present an algorithm for speech deconvolution, where the dynamic range of the convolutive speech is also used as the prior information. In this algorithm, the estimation of the impulse response and the source signal is achieved by alternating between two steps, namely, the ℓ1 regularized least squares optimization and a proximal operation. As demonstrated in our experiments, the proposed method pro- vides superior performance for deconvolution of a sparse acoustic system, as compared with two state-of-the-art methods
Breaking the Limits -- Redefining the Instantaneous Frequency

The Carson and Fry (1937) introduced the concept of variable frequency as a
generalization of the constant frequency. The instantaneous frequency (IF) is
the time derivative of the instantaneous phase and it is well-defined only when
this derivative is positive. If this derivative is negative, the IF creates
problem because it does not provide any physical significance. This study
proposes a mathematical solution and eliminate this problem by redefining the
IF such that it is valid for all monocomponent and multicomponent signals which
can be nonlinear and nonstationary in nature. This is achieved by using the
property of the multivalued inverse tangent function. The efforts and
understanding of all the methods based on the IF would improve significantly by
using this proposed definition of the IF. We also demonstrate that the
decomposition of a signal, using zero-phase filtering based on the well
established Fourier and filter theory, into a set of desired frequency bands
with proposed IF produces accurate time-frequency-energy (TFE) distribution
that reveals true nature of signal. Simulation results demonstrate the efficacy
of the proposed IF that makes zero-phase filter based decomposition most
powerful, for the TFE analysis of a signal, as compared to other existing
methods in the literature.Comment: 12 pages, 15 figures. arXiv admin note: text overlap with
  arXiv:1604.0499
Restoration of montane fen meadows by mowing remains possible after 4 - 35 years of abandonment

The abandonment of management in Swiss fen meadows has reduced their plant species diversity and the fitness of some typical fen species. We examined whether the resumption of mowing can reverse these effects, and if so, which mechanisms are responsible for community change; we also tested whether restoration success depends on the duration since abandonment. Experimental mowing was applied to 15 montane fen meadows of NE Switzerland that had been abandoned for 4–35 years. After two years of mowing, plant species richness was 11% higher in mown plots (2 m2) than in fallow plots, approaching levels of neighbouring continuously managed fen meadows. In particular, experimental mowing significantly increased the number of fen indicator species (+15%) as well as herbs and woody species (seedlings and saplings), while grass, sedge and rush species richness was not affected. Mowing had little effect on aboveground biomass, but strongly reduced litter mass (-50%) and canopy height (-20%). Seedling densities of two common species showed opposite responses to mowing: they increased in Carex davalliana and decreased in Succisa pratensis, approaching values of continuously mown fen meadows. Duration since abandonment had no significant effect on any of the variables. Our results demonstrate a rapid recovery of montane fen plant communities irrespective of the duration since abandonment (up to 35 years). We conclude that the restoration of pre-fallow plant community composition is likely to be successful if site conditions (hydrology, nutrient status) remain intact and if common habitat specialists are still present in the vegetation and/or seed bank
Seed dispersal distances: a typology based on dispersal modes and plant traits

The ability of plants to disperse seeds may be critical for their survival under the current constraints of landscape fragmentation and climate change. Seed dispersal distance would therefore be an important variable to include in species distribution models. Unfortunately, data on dispersal distances are scarce, and seed dispersion models only exist for some species with particular dispersal modes. To overcome this lack of knowledge, we propose a simple approach to estimate seed dispersal distances for a whole regional flora. We reviewed literature about seed dispersal in temperate regions and compiled data for dispersal distances together with information about the dispersal mode and plant traits. Based on this information, we identified seven "dispersal types" with similar dispersal distances. For each type, upper limits for the distance within which 50% and 99% of a species' seeds will disperse were estimated with the 80th percentile of the available values. These distances varied 5000-fold among the seven dispersal types, but generally less than 50-fold within the types. Thus, our dispersal types represented a large part of the variation in observed dispersal distances. The attribution of a dispersal type to a particular species only requires information that is already available in databases for most Central European species, i.e. dispersal vector (e.g. wind, animals), the precise mode of dispersal (e.g. dyszoochory, epizoochory), and species traits influencing the efficiency of dispersal (e.g. plant height, typical habitats). This typology could be extended to other regions and will make it possible to include seed dispersal in species distribution models
Biomass production of the last remaining fen with Saxifraga hirculus in Switzerland is controlled by nitrogen availability

For conservation management of endangered plants it is important to know which nutrient(s) control growth of the vegetation, because maintenance of low nitrogen (N), phosphorus (P) or potassium (K) availability requires different management measures. The aim of this study was to determine the type of nutrient limitation for the vegetation in the last remaining site with Saxifraga hirculus in Switzerland, using nutrient ratios in the aboveground vegetation as an indicator. We made vegetation relevees, collected biomass of the vascular plants, and took soil samples in three plots at this site. The biomass was very low (152-231 g m-2), and all three plots were clearly N-limited with N:P ratios of 7-8. Soil extractable N concentrations were generally low, and P and K concentrations were moderate to high, which was consistent with the indicated N limitation. Hence conservation management first of all needs to prevent N-enrichment, and needs to avoid increased mineralization rates through drainage, or the accumulation of N in the system from atmospheric deposition. Therefore N output seems required through for instance grazing or mowing. The current grazing management seems to function well, since total aboveground biomass is very low and S. hirculus has a high abundance in this last remnant