Stochastic resonance in sequential detectors
Stochastic resonance (SR) is a nonlinear phenomenon known in physics that has attracted recent interest in the signal-processing literature, and specifically in the context of detection. We investigate the SR effect arising in sequential detectors for ...
Distributed detection in the presence of Byzantine attacks
Distributed detection in the presence of cooperative (Byzantine) attack is considered. It is assumed that a fraction of the monitoring sensors are compromised by an adversary, and these compromised (Byzantine) sensors are reprogrammed to transmit ...
Vehicle speed estimation using acoustic wave patterns
We estimate a vehicle's speed, its wheelbase length, and tire track length by jointly estimating its acoustic wave pattern with a single passive acoustic sensor that records the vehicle's drive-by noise. The acoustic wave pattern is determined using the ...
Detection of multiple changes in fractional integrated ARMA processes
This paper addresses the problem of changepoint detection in FARIMA processes. The received signal is modeled as a FARIMA process, with abrupt changes in the Hurst and ARMA parameters. The proposed changepoint detection method first estimates the model ...
Estimation of the parameters of sinusoidal signals in non-Gaussian noise
Accurate estimation of the amplitude and frequency parameters of sinusoidal signals from noisy observations is an important problem in many signal processing applications. In this paper, the problem is investigated under the assumption of non-Gaussian ...
Performance limits of alphabet diversities for FIR SISO channel identification
Finite impulse responses (FIR) of single-input single-output (SISO) channels can be blindly identified from second-order statistics of transformed data, for instance when the channel is excited by binary phase shift keying (BPSK), minimum shift keying (...
Data-driven spatio-temporal modeling using the integro-difference equation
A continuous-in-space, discrete-in-time dynamic spatio-temporal model known as the Integro-Difference Equation (IDE) model is presented in the context of data-driven modeling. A novel decomposition of the IDE is derived, leadmg to state-space ...
Multitask compressive sensing
Compressive sensing (CS) is a framework whereby one performs N nonadaptive measurements to constitute a vector v ∈ RN, with v used to recover an approximation û ∈ RM to a desired signal u ∈ RM, with N ≪ M; this is performed under the assumption that u. ...
A stochastic model for a pseudo affine projection algorithm
This paper presents a statistical analysis of a Pseudo Affine Projection (PAP) algorithm, obtained from the Affine Projection algorithm (AP) for a step size α < 1 and a scalar error signal in the weight update. Deterministic recursive equations are ...
Stability and convergence analysis of transform-domain LMS adaptive filters with second-order autoregressive process
In this paper, the stability and convergence properties of the class of transform-domain least mean square (LMS) adaptive filters with second-order autoregressive (AR) process are investigated. It is well known that this class of adaptive filters ...
Overcomplete discrete wavelet transforms with rational dilation factors
This paper develops an overcomplete discrete wavelet transform (DWT) based on rational dilation factors for discrete-time signals. The proposed overcomplete rational DWT is implemented using self-inverting FIR filter banks, is approximately shift-...
Higher-order properties of analytic wavelets
The influence of higher-order wavelet properties on the analytic wavelet transform behavior is investigated, and wavelet functions offering advantageous performance are identified. This is accomplished through detailed investigation of the generalized ...
A fast convergence algorithm for band-limited extrapolation by sampling
In this paper, an algorithm for band-limited extrapolation is presented. This uses Shannon's sampling theorem and Fourier series. Error analysis is given by proof. The convergence rate is much faster than that of the Papoulis-Gerchberg algorithm. The ...
Functionally weighted lagrange interpolation of band-limited signals from nonuniform samples
A modification of the conventional Lagrange interpolator is proposed in this paper, that allows one to approximate a band-limited signal from its own nonuniform samples with high accuracy. The modification consists in applying the Lagrange method to the ...
On the accuracy and resolution of powersum-based sampling methods
Recently, several sampling methods suitable for signals that are sums of Diracs have been proposed. Though they are implemented through different acquisition architectures, these methods all rely on estimating the parameters of a powersum series. We ...
Random sampling estimates of Fourier transforms: antithetical stratified Monte Carlo
We estimate the Fourier transform of continuous-time signals on the basis of N discrete-time nonuniform observations. We introduce a class of antithetical stratified random sampling schemes and we obtain the performance of the corresponding estimates. ...
Algebraic signal processing theory: Cooley-Tukey type algorithms for real DFTs
In this paper, we systematically derive a large class of fast general-radix algorithms for various types of real discrete Fourier transforms (real DFTs) including the discrete Hartley transform (DHT) based on the algebraic signal processing theory. This ...
Variational Bayesian inference for a nonlinear forward model
Variational Bayes (VB) has been proposed as a method to facilitate calculations of the posterior distributions for linear models, by providing a fast method for Bayesian inference by estimating the parameters of a factorized approximation to the ...
A novel adaptive nonlinear filter-based pipelined feed-forward second-order Volterra architecture
Due to the computational complexity of the Volterra filter there are limitations on the implementation in practice. In this paper, a novel adaptive joint process filter using pipelined feedforward second-order Volterra architecture (JPPSOV) to reduce ...
Influence function and asymptotic efficiency of scatter matrix based array processors: case MVDR beamformer
In this paper, we consider array processors that are scale-invariant functions of the array covariance matrix. The emphasis is on Capon's MVDR beamformer. We call such an array processor as scatter matrix based (SMB) array processor since the covariance ...
A novel subspace approach for cooperative localization in wireless sensor networks using range measurements
Estimating the positions of sensor nodes is a fundamental and crucial problem in wireless sensor networks. In this paper, three novel subspace methods for node localization in a fully connected network are devised with the use of range measurements. ...
Tail extrapolation in MLSE receivers using nonparametric channel model estimation
This paper presents a method for determining the probability of rare events, in particular for probability density function (pdf) and bit error rate (BER) estimation. The derivation of the method is based on the presumption that the pdf is a member of a ...
Resource-scalable joint source-channel MAP and MMSE estimation of multiple descriptions
A joint source-channel multiple description (JSC-MD) framework for signal estimation and communication in resource-constrained lossy networks is presented. To keep the encoder complexity at a minimum, a signal is coded by a multiple description ...
A fast approach for overcomplete sparse decomposition based on smoothed l0 norm
In this paper, a fast algorithm for overcomplete sparse decomposition, called SL0, is proposed. The algorithm is essentially a method for obtaining sparse solutions of underdetermined systems of linear equations, and its applications include under-...
Constrained adaptive echo cancellation for discrete multitone systems
In communication systems where full-duplex transmission is required, echo cancellers are deployed to cancel the interference of the transmitted signal at the collocated receiver. For systems using discrete multitone (DMT) modulation, echo cancel lation ...
Low-complexity variable step-size mechanism for code-constrained constant modulus stochastic gradient algorithms applied to CDMA interference suppression
The code-constrained constant modulus algorithm (CCM) implemented with a stochastic gradient (SG) technique is a very effective and efficient blind approach for interference suppression when a communication channel is frequency-selective. In ...
On source transmission over MIMO channels with limited feedback
The problem of source-channel coding over a multiple-antenna (MIMO) channel with quantized channel state information at the transmitter (CSIT) is considered. Upper bounds on the distortion exponents achieved with partial CSIT under a long-term power ...
Polynomial filtering for fast convergence in distributed consensus
In the past few years, the problem of distributed consensus has received a lot of attention, particularly in the framework of ad hoc sensor networks. Most methods proposed in the literature address the consensus averaging problem by distributed linear ...
Distributed consensus algorithms in sensor networks with imperfect communication: link failures and channel noise
The paper studies average consensus with random topologies (intermittent links) and noisy channels. Consensus with noise in the network links leads to the bias-variance dilemma-running consensus for long reduces the bias of the final average estimate ...