Diffusion least‐mean P‐power algorithms for distributed estimation in alpha‐stable noise environments

Diffusion Least Mean P-Power Algorithms for Distributed Estimation in Alpha-Stable Noise Environments

Introduction: Emergent wireless sensor networks based applications have motivated the development of distributed adaptive estimation schemes. Distributed least mean squares (LMS) [1] and recursive least squares (RLS) type algorithms have received more attentions [2]. Readers can refer to [3] and the references therein for details about up to date diffusion strategies for adaptation and learning...

A Robust Distributed Estimation Algorithm under Alpha-Stable Noise Condition

Robust adaptive estimation of unknown parameter has been an important issue in recent years for reliable operation in the distributed networks. The conventional adaptive estimation algorithms that rely on mean square error (MSE) criterion exhibit good performance in the presence of Gaussian noise, but their performance drastically decreases under impulsive noise. In this paper, we propose a rob...

Noise estimation for diffusion weighted MR image

Noise estimation Algorithms for Speech Enhancement in highly non-stationary Environments

A noise estimation algorithm plays an important role in speech enhancement. Speech enhancement for automatic speaker recognition system, Man–Machine communication, Voice recognition systems, speech coders, Hearing aids, Video conferencing and many applications are related to speech processing. All these systems are real world systems and input available for these systems is only the noisy speec...

Weighted diffusion LMP algorithm for distributed estimation in non-uniform noise conditions

This letter presents an improved version of diffusion least mean ppower (LMP) algorithm for distributed estimation. Instead of sum of mean square errors, a weighted sum of mean square error is defined as the cost function for global and local cost functions of a network of sensors. The weight coefficients are updated by a simple steepest-descent recursion to minimize the error signal of the glo...