Ali H. Sayed

Bio: Ali H. Sayed is an academic researcher from École Polytechnique Fédérale de Lausanne. The author has contributed to research in topics: Adaptive filter & Optimization problem. The author has an hindex of 81, co-authored 728 publications receiving 36030 citations. Previous affiliations of Ali H. Sayed include Harbin Engineering University & University of California, Los Angeles.

Adaptive sigma-delta modulation with improved dynamic range

Abstract: An adaptive sigma-delta modulation and demodulation technique, wherein a quantizer step-size is adapted based on estimates of an input signal to the quantizer, rather than on estimates of an input signal to the modulator.

An optimal error nonlinearity for robust adaptation against impulsive noise

Abstract: The least-mean squares algorithm is non-robust against impulsive noise. Incorporating an error nonlinearity into the update equation is one useful way to mitigate the effects of impulsive noise. This work develops an adaptive structure that parametrically estimates the optimal error-nonlinearity jointly with the parameter of interest, thus obviating the need for a priori knowledge of the noise probability density function. The superior performance of the algorithm is established both analytically and experimentally.

A robust minimum-variance filter for time varying uncertain discrete-time systems

Abstract: A robust filter is designed for uncertain discrete time models. The filter is based on a regularized solution and guarantees minimum state error variance. Simulation results confirm its superior performance over other robust filter designs.

Robust distributed detection over adaptive diffusion networks

Abstract: Diffusion adaptation techniques based on the least-mean-squares criterion have been proposed for distributed detection of a signal in Gaussian-distributed noise, forgoing the need for a fusion center. However, least-mean-squares solutions are generally non-robust against impulsive noise. In this work, we combine nonlinear filtering with diffusion adaptation and propose a strategy for distributed detection in the presence of impulsive noise. The superiority of the algorithm is validated experimentally.

Clock jitter estimation in noise

Abstract: Clock timing jitter refers to random perturbations in the sampling time in analog-to-digital converters (ADCs). The perturbations are caused by circuit imperfections in the sampling clock. This paper analyzes the effect of sampling clock jitter on the acquired samples in the midst of quantization noise and random Gaussian noise. The paper proposes a method for estimating the jitter for cognitive radio architectures at high sampling rates. The paper also examines the fixed-point implementation of the algorithm and its theoretical performance.

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

Tensor Decompositions and Applications

Abstract: This survey provides an overview of higher-order tensor decompositions, their applications, and available software. A tensor is a multidimensional or $N$-way array. Decompositions of higher-order tensors (i.e., $N$-way arrays with $N \geq 3$) have applications in psycho-metrics, chemometrics, signal processing, numerical linear algebra, computer vision, numerical analysis, data mining, neuroscience, graph analysis, and elsewhere. Two particular tensor decompositions can be considered to be higher-order extensions of the matrix singular value decomposition: CANDECOMP/PARAFAC (CP) decomposes a tensor as a sum of rank-one tensors, and the Tucker decomposition is a higher-order form of principal component analysis. There are many other tensor decompositions, including INDSCAL, PARAFAC2, CANDELINC, DEDICOM, and PARATUCK2 as well as nonnegative variants of all of the above. The N-way Toolbox, Tensor Toolbox, and Multilinear Engine are examples of software packages for working with tensors.

Random graphs

Abstract: We will review some of the major results in random graphs and some of the more challenging open problems. We will cover algorithmic and structural questions. We will touch on newer models, including those related to the WWW.

Table Of Integrals Series And Products

Abstract: Thank you very much for downloading table of integrals series and products. Maybe you have knowledge that, people have look hundreds times for their chosen books like this table of integrals series and products, but end up in harmful downloads. Rather than reading a good book with a cup of coffee in the afternoon, instead they cope with some harmful virus inside their laptop. table of integrals series and products is available in our book collection an online access to it is set as public so you can get it instantly. Our book servers saves in multiple locations, allowing you to get the most less latency time to download any of our books like this one. Merely said, the table of integrals series and products is universally compatible with any devices to read.