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This paper presents a new method for the blind separation of sparse sources whose number N can exceed the number of sensors M. Recently, sparseness based blind separation has been actively studied. However, most methods utilize a linear sensor array (or only two sensors), and therefore have certain limitations; e.g., they cannot be applied to symmetrically positioned sources. To allow the use of more...
We consider the detection of a signal in the presence of both interferences that lie in a known subspace and white noise. The signal to be detected is the product of an unknown amplitude and a known signature-vector that is itself subject to additive white Gaussian noise. We develop the maximum likelihood estimates (MLE) of the problem in order to apply the generalized maximum likelihood test (GLRT)...
This contribution deals with channel estimation and frequency ambiguity resolution in a MIMO OFDM context. Existing blind frequency-recovery algorithms for OFDM are able to provide a reliable estimate of the frequency offset up to an integer multiple of the subcarrier spacing. To resolve the remaining ambiguity, one can employ either pilot symbols or the unknown coded data symbols. Clearly, the latter...
This paper addresses the problem of detecting significant intensity variations in multiple Poissonian time-series. This detection is achieved by using a constant Poisson rate model and a hierarchical Bayesian approach. An appropriate Gibbs sampling strategy allows joint estimation of the unknown parameters and hyperparameters. An extended model that includes constraints on the segment lengths is also...
This paper proposes a novel semi-blind space-time equalization method for wireless Multiple-Input Multiple-Output (MIMO) spatial multiplexing systems using Single-Carrier Cyclic-Prefix (SC-CP) block transmissions. Independent Component Analysis (ICA) is employed to track the time-varying MIMO channel. It is shown that with a training overhead of only 0.05%, the proposed method can provide close performance...
This paper describes a multiple description coding (MDC) of images, introducing a phase scrambling with the adjustable dispersion extent of sample value. Whereas a phase scrambling gains robustness to transmission errors, it loses the time-localized information. Consequently, when this phase scrambling process is combined with a wavelet-based coder for the MDC, its objective coding performance is...
In this paper we interpret the statistics of ultrasonic backscatter in the framework of a normal variance-mean mixture model. This is done by considering the complex envelope of the echo signal as a double stochastic circular Gaussian variable, in which both the variance and the mean are linearly scaled by a stochastic factor Z. By assuming Z to be Γ distributed, we re-derive the generalized K distribution,...
This paper presents an analytical framework for the performance evaluation of an MC-CDMA forward-link in the presence of nonlinear distortions induced by transmitter's high-power amplifiers. The statistical characterization of the decision variable used for data detection is carried out through the application of the Bussgang theorem. Simulation results validate the accuracy of the proposed method...
In wireless adhoc and sensor networks a close synergy and coordination is required among entities at different layers of the network architecture to achieve the robust behavior that is expected from these systems in the potentially harsh environments where they may operate. The volatile wireless channel, the unpredictability of traffic due to unknown traffic generation scenarios as well as variability...
We propose low-complexity equalizers for multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems in frequency-selective time-varying channels, by extending the approach we formerly proposed for single-antenna OFDM systems. Specifically, by neglecting the intercarrier interference (ICI) coming from faraway subcarriers, we design minimum mean-squared error (MMSE)...
Combining spatial multiplexing with linear unitary precoding allows for high data rates, but requires a feedback link from the receiver to the transmitter. We focus on quantizing and feeding back the precoder itself, since it outperforms quantized channel feedback. More specifically, we propose a modified precoder quantization approach that outperforms the conventional one. We investigate both the...
This paper explores properties of the spiking neuron model of auditory nerve fiber. As it results from the described reasoning, the model response in a form of the spike sequence is in fact a first-order Markov chain of certain non-overlapping sub-sequences, which, being taken separately, encode the incoming signal on the corresponding time intervals. This observation comes as a direct consequence...
We consider the problem of deconvolving an image with a priori information on its representation in a frame. Our variational approach consists of minimizing the sum of a residual energy and a separable term penalizing each frame coefficient individually. This penalization term may model various properties, in particular sparsity. A general iterative method is proposed and its convergence is established...
We have investigated two different strategies to improve the quality of ISAR images corrupted by Gaussian noise. The images are generated using a Time Frequency technique known as Atomic Decomposition (AD). The first strategy is a classical denoising technique based on an AD detector developed for signal detection in noise. The second technique separates the atoms extracted through AD by their parameters...
The standard MVDR beamformer has high resolution and interference rejection capability when the array steering vector is accurately known. However, it is known to degrade if steering vector error exists. Motivated by recent work in robust adaptive beamforming, we develop variants of the constrained robust adaptive beamformer that attempt to limit the search in the underlying optimization problem to...
In this paper, we present a novel recursive method for pixel-based motion estimation. Assuming small displacements, we use an adaptive LMS filtering scheme to match the intensity values and calculate the displacement between two adjacent video frames. Using a sliding window from the template image, the proposed algorithm employs a simple 2-D LMS filter to adapt the corresponding set of coefficients...
Phase noise causes significant degradation in the performance of Orthogonal Frequency Division Multiplexing (OFDM) based wireless communication systems. In the proposed compensation scheme, the communication between the transmitter and receiver blocks consists of two stages. In the first stage, block-type pilot symbols are transmitted and the channel coefficients are jointly estimated with the phase...
Particle filters have recently been applied to speech enhancement when the input speech signal is modeled as a time-varying autoregressive process with stochastically evolving parameters. This type of modeling results in a nonlinear and conditionally Gaussian state-space system that is not amenable to analytical solutions. Prior work in this area involved signal processing in the fullband domain and...
In this paper, an efficient method to implement undecimated directional filter banks (UDFBs) is proposed. The method is based on an observation that many non-separable two-dimensional two-channel FBs can be efficiently implemented by a separable structure if their polyphase components are separable. Therefore, with appropriate delay and advance blocks, undecimated non-separable FBs can be computed...
Pre-equalization of MIMO systems is required for a wide variety of applications, e. g. in channel equalization and spatial sound reproduction. However, traditional adaptive algorithms fail for channel numbers of some ten or more. It is shown that the problem becomes tractable by decoupling of the MIMO adaptation problem, e. g. by a generalized singular value decomposition. This method is called eigenspace...
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