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.

Bio-Inspired Decentralized Radio Access Based on Swarming Mechanisms Over Adaptive Networks

Abstract: The goal of this paper is to study the learning abilities of adaptive networks in the context of cognitive radio networks and to investigate how well they assist in allocating power and communications resources in the frequency domain The allocation mechanism is based on a social foraging swarm model that lets every node allocate its resources (power/bits) in the frequency regions where the interference is at a minimum while avoiding collisions with other nodes We employ adaptive diffusion techniques to estimate the interference profile in a cooperative manner and to guide the motion of the swarm individuals in the resource domain A mean square performance analysis of the proposed strategy is provided and confirmed by simulation results The proposed approach endows the cognitive network with powerful learning and adaptation capabilities, allowing fast reaction to dynamic changes in the spectrum Numerical examples show how cooperative spectrum sensing remarkably improves the performance of the resource allocation technique based on swarming

Capacity enhancement in coherent optical MIMO (COMIMO) multimode fiber links

Abstract: In this paper, we study a coherent optical MIMO (COMIEMO) multi-mode fiber link proposed for enhancing the fiber information capacity. We examine the statistical characterization of the equivalent MIMO channel and the improvement in the fiber capacity due to MIMO transmission. It is shown that the equivalent channel behaves similarly to a complex Gaussian MIMO channel, suggesting that the available results on wireless MIMO communication systems can be applied to optical fiber links for capacity enhancement.

Extended Chandrasekhar recursions

Abstract: We extend the discrete-time Chandrasekhar recursions for least-squares estimation in constant parameter state-space models to a class of structured time-variant state-space models, special cases of which often arise in adaptive filtering. It can be shown that the much studied exponentially weighted recursive least-squares filtering problem can be reformulated as an estimation problem for a state-space model having this special time-variant structure. Other applications arise in the multichannel and multidimensional adaptive filtering context. >

Learning over social networks via diffusion adaptation

Abstract: We propose a diffusion strategy to enable social learning over networks Individual agents observe signals influenced by the state of the environment The individual measurements are not sufficient to enable the agents to detect the true state of the environment on their own Agents are then encouraged to cooperate through a diffusive process of self-learning and social-learning We show that the diffusion algorithm converges almost surely to the true state Simulation results also illustrate the superior convergence rate of the diffusion strategy over consensus-based strategies since diffusion schemes allow information to diffuse more thoroughly through the network

Optimal combination rules for adaptation and learning over networks

Abstract: Adaptive networks, consisting of a collection of nodes with learning abilities, are well-suited to solve distributed inference problems and to model various types of self-organized behavior observed in nature. One important issue in designing adaptive networks is how to fuse the information collected from the neighbors, especially since the mean-square performance of the network depends on the choice of combination weights. We consider the problem of optimal selection of the combination weights and motivate one combination rule, along with an adaptive implementation. The rule is related to the inverse of the noise variances and is shown to be effective in simulations.

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.