We propose a best basis algorithm for signal enhancement in white Gaussian noise. The best basis search is performed in families of orthonormal bases constructed with wavelet packets or local cosine bases. We base our search for the “best” basis on a criterion of minimal reconstruction error of the underlying signal. This approach is intuitively appealing because the enhanced or estimated signa...

One of the key differences between one-dimensional (1-D) and N -D (N ≥ 2) signals is the geometrical information, an important and unique feature of multidimensional signals. The goal of this research is to develop a new set of theories and techniques in signal processing that can make better use of the intrinsic geometrical information in multidimensional data in a robust and efficient way. Th...

This thesis presents a signal representation in terms of operators The signal is as sumed to be an element of a vector space and subject to transformations of operators The operators form continuous groups so called Lie groups The representation can be used for signals in general in particular if spatial relations are unde ned and it does not require a basis of the signal space to be useful Spe...

Traditional signal decompositions such as transforms, filterbanks, and wavelets generate signal expansions using the analysis–synthesis setting: The expansion coefficients are found by taking the inner product of the signal with the corresponding analysis vector. In this paper, we try to free ourselves from the analysis–synthesis paradigm by concentrating on the synthesis or reconstruction part...

Abstract : In this paper we show that a complex dynamic representation (logenvelope and instantaneous frequency) can be used efficiently to compress the spectrum and band−shift a discrete−time signal. The original method and algorithm conceived here do not violate the amplitude−phase relationships typical of natural sound signals. This is achieved by simultaneous modification via transmapping o...

This work presents a framework for wavelet-based representation of a given deterministic signal. We propose a method for matched wavelet based representation of the signal. Our method requires a signalconditioning step at each stage of the wavelet decomposition. The wavelet system designed in this work is biorthogonal. Both the signal-conditioning step and the wavelet system depend on the given...

Ab8tmctWe examine the representation of signals by the Wavelet 'lhansform Modulus Maxima together with the alternating projection reconstruction algorithm proposed by Mallat. We show that the projection algorithm of Mallat is not minimum distance and not necessarily nonexpansive. Convergence is therefore not guaranteed. We describe an alternative projection operator which is minimum distance an...

MOTIVATIONS Signal transduction is the common term used to define a diverse topic that encompasses a large body of knowledge about the biochemical mechanisms. Since most of the knowledge of signal transduction resides in scientific articles and is represented by texts in natural language or by diagrams, there is the need of a knowledge representation model for signal transduction pathways that ...

The propagation of visual signals from individual cone photoreceptors through parallel neural circuits was examined in the primate retina. Targeted stimulation of individual cones was combined with simultaneous recording from multiple retinal ganglion cells of identified types. The visual signal initiated by an individual cone produced strong responses with different kinetics in three of the fo...