This paper studies the problem of recovering a signal with a sparse representation in a given orthonormal basis using as few noisy observations as possible. As opposed to previous studies, this paper models observations which are subject to the type of ‘clutter noise’ encountered in radar applications (i.e., the measurements used influence the observed noise). Given this model, the paper develo...

We analyze the effect of a heterogeneous variance on bump detection in a Gaussian regression model. To this end we allow for a simultaneous bump in the variance and specify its impact on the difficulty to detect the null signal against a single bump with known signal strength. This is done by calculating lower and upper bounds, both based on the likelihood ratio. Lower and upper bounds together...

Noise cancellation in the field of Adaptive filtering has become the essential requirement of the signal processing .The standard multilayer perceptron (MLP) model of Neural Networks is now popular in Adaptive filtering This paper presents the noise-cancellation technique based on Generalized-mean neuron network (GMN). This network consists of an aggregation function, which is based on the gene...

Based on a modifled Bernoulli-Gaussian model, we propose an adaptive maximum-likelihood channel equalizer, which is a block signal processing algorithm, for the detection of binary sequences transmitted through an unknown slowly time-varying channel. Both computational load and storage required by the proposed adaptive channel equalizer are linearly rather than exponentially proportional to the...

This paper presents a new approach for human cataract automatical detection based on ultrasound signal processing. Two signal decomposition techniques, empirical mode decomposition and discrete wavelet transform are used in the presented method. Performance comparison of these two decomposition methods when applied to this specific ultrasound signal is given. Described method includes ultrasoni...

A monitoring approach to the problem of constructing fault-tolerant and adaptive real-time systems, based on the fail-signal processor, is described. Low error detection latency time is a primary goal. A fail-signal processor comprises an application processor along with a simple monitoring processor that detects abnormal functional or timing behaviour in the application processor; on such a fa...

In many signal processing applications, adaptive frequency estimation and tracking of noisy narrowband signals is often required in communications, radar, sonar, controls, biomedical signal processing, and the applications such as detection of a noisy sinusoidal signal and cancellation of periodic signals. In order to achieve the objective of frequency tracking and estimation, an adaptive finit...