An improved generalized inverse algorithm for linear inequalities and its applications

Iterative, two-class algorithm for linear inequalitie

Convolutional compressed sensing using deterministic sequences

This is the author's accepted manuscript (with working title "Semi-universal convolutional compressed sensing using (nearly) perfect sequences"). The final published article is available from the link below. Copyright @ 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.In this paper, a new class of orthogonal circulant matrices built from deterministic sequences is proposed for convolution-based compressed sensing (CS). In contrast to random convolution, the coefficients of the underlying filter are given by the discrete Fourier transform of a deterministic sequence with good autocorrelation. Both uniform recovery and non-uniform recovery of sparse signals are investigated, based on the coherence parameter of the proposed sensing matrices. Many examples of the sequences are investigated, particularly the Frank-Zadoff-Chu (FZC) sequence, the m-sequence and the Golay sequence. A salient feature of the proposed sensing matrices is that they can not only handle sparse signals in the time domain, but also those in the frequency and/or or discrete-cosine transform (DCT) domain

Asymptotically Universal Crossover in Perturbation Theory with a Field Cutoff

We discuss the crossover between the small and large field cutoff (denoted x_{max}) limits of the perturbative coefficients for a simple integral and the anharmonic oscillator. We show that in the limit where the order k of the perturbative coefficient a_k(x_{max}) becomes large and for x_{max} in the crossover region, a_k(x_{max}) is proportional to the integral from -infinity to x_{max} of e^{-A(x-x_0(k))^2}dx. The constant A and the function x_0(k) are determined empirically and compared with exact (for the integral) and approximate (for the anharmonic oscillator) calculations. We discuss how this approach could be relevant for the question of interpolation between renormalization group fixed points.Comment: 15 pages, 11 figs., improved and expanded version of hep-th/050304

Learning algorithms for multi-class pattern classification and problems associated with on-line handwritten character recognition

On-line handwritten alphanumeric character recognition system and learning algorithm for multiclass pattern classificatio

Engineering a Conformant Probabilistic Planner

We present a partial-order, conformant, probabilistic planner, Probapop which competed in the blind track of the Probabilistic Planning Competition in IPC-4. We explain how we adapt distance based heuristics for use with probabilistic domains. Probapop also incorporates heuristics based on probability of success. We explain the successes and difficulties encountered during the design and implementation of Probapop