2 citations · 5 across the 12 of their papers we have counts for
6 papers · 1 filter
A new technique for compression of data sets
Anatoli Torokhti
Data compression techniques are characterized by four key performance indices which are (i) associated accuracy, (ii) compression ratio, (iii) computational work, and (iv) degree o…
Processing of large sets of stochastic signals: filtering based on piecewise interpolation technique
Anatoli Torokhti
Suppose and are large sets of observed and reference signals, respectively, each containing signals. Is it possible to construct a filter that requires a…
Data Compression: Multi-Term Approach
Pablo Soto-Quiros, Anatoli Torokhti
In terms of signal samples, we propose and justify a new rank reduced multi-term transform, abbreviated as MTT, which, under certain conditions, may provide better-associated accur…
Second Degree Model for Multi-Compression and Recovery of Distributed Signals
Pablo Soto-Quiros, Anatoli Torokhti, Stanley J. Miklavcic
We study the problem of multi-compression and reconstructing a stochastic signal observed by several independent sensors (or compressors) that transmit compressed information to a…
Extended Principal Component Analysis
Pablo Soto-Quiros, Anatoli Torokhti
Principal Component Analysis (PCA) is a transform for finding the principal components (PCs) that represent features of random data. PCA also provides a reconstruction of the PCs t…
Interpolation Estimator for Infinite Sets of Random Vectors
Anatoli Torokhti
We propose an approach to the estimation of infinite sets of random vectors. The problem addressed is as follows. Given two infinite sets of random vectors, find a single estimator…