A highly modular adaptive lattice algorithm for multichannel least squares filtering

In this paper a highly modular adaptive lattice algorithm for multichannel least squares FIR filtering and multivariable system identification is presented. Multichannel filters with different number of delay elements per input channel are allowed. The main features of the proposed multichannel adaptive lattice least squares algorithm is the use of scalar only operations, multiplications/divisions and additions, and the local communication which enables the development of a fully pipelining architecture. The tracking capability and the numerical stability and accuracy of the proposed technique are illustrated by simulations

Architectures for block Toeplitz systems

In this paper efficient VLSI architectures of highly concurrent algorithms for the solution of block linear systems with Toeplitz or near-to-Toeplitz entries are presented. The main features of the proposed scheme are the use of scalar only operations, multiplications/divisions and additions, and the local communication which enables the development of wavefront array architecture. Both the mean squared error and the total squared error formulations are described and a variety of implementations are given

Blind identification of bilinear systems

Journal ArticleAbstract-This paper is concerned with the blind identification of a class of bilinear systems excited by non-Gaussian higher order white noise. The matrix of coefficients of mixed input-output terms of the bilinear system model is assumed to be triangular in this work. Under the additional assumption that the system output is corrupted by Gaussian measurement noise, we derive an exact parameter estimation procedure based on the output cumulants of orders up to four. Results of the simulation experiments presented in the paper demonstrate the validity and usefulness of our approach

Asymptotic Achievability of the Cramér–Rao Bound For Noisy Compressive Sampling

We consider a model of the form ${bf y}={bf Ax}+{bf n}$, where ${bf x}inBBC^{M}$ is sparse with at most $L$ nonzero coefficients in unknown locations, ${bf y}inBBC^{N}$ is the observation vector, ${bf A}inBBC^{Ntimes M}$ is the measurement matrix and ${bf n}inBBC^{N}$ is the Gaussian noise. We develop a CramÉr–Rao bound on the mean squared estimation error of the nonzero elements of ${bf x}$, corresponding to the genie-aided estimator (GAE) which is provided with the locations of the nonzero elements of ${bf x}$. Intuitively, the mean squared estimation error of any estimator without the knowledge of the locations of the nonzero elements of ${bf x}$ is no less than that of the GAE. Assuming that $L/N$ is fixed, we establish the existence of an estimator that asymptotically achieves the CramÉr–Rao bound without any knowledge of the locations of the nonzero elements of ${bf x}$ as $Nrightarrowinfty$ , for ${bf A}$ a random Gaussian matrix whose elements are drawn i.i.d. according to ${cal N}(0,1)$ .Engineering and Applied Science

Adaptive Greedy Algorithm With Application to Nonlinear Communications

Greedy algorithms form an essential tool for compressed sensing. However, their inherent batch mode discourages their use in time-varying environments due to significant complexity and storage requirements. In this paper two existing powerful greedy schemes developed in the literature are converted into an adaptive algorithm which is applied to estimation of a class of nonlinear communication systems. Performance is assessed via computer simulations on a variety of linear and nonlinear channels; all confirm significant improvements over conventional methods.Engineering and Applied Science

Modifying Boolean Functions to Ensure Maximum Algebraic Immunity

The algebraic immunity of cryptographic Boolean functions is studied in this paper. Proper modifications of functions achieving maximum algebraic immunity are proved, in order to yield new functions of also maximum algebraic immunity. It is shown that the derived results apply to known classes of functions. Moreover, two new efficient algorithms to produce functions of guaranteed maximum algebraic immunity are developed, which further extend and generalize known constructions of functions with maximum algebraic immunity