An accurate and computationally efficient means of classifying myoelectric signal (MES) patterns has been the subject of considerable research effort in recent years. Effective feature extraction is crucial to reliable classification and, in the quest to improve the accuracy of transient MES pattern classification, many forms of signal representation have been suggested. It is shown that featur...

A key issue in the development of next generation intelligent systems is the ability to perceive and understand the complex environments in which they will operate Complex environments are characterized by variable signal to noise ratios unpredictable source be havior and the simultaneous occurrence of target sources whose signal signatures can over lap mask or otherwise distort each other This...

This paper presents a unifying theory for many concepts and operations encountered in or related to morphological image and signal analysis. This unification requires a set-theoretic melhodology, where signals are modeled as sets, systems (signal transformations) are viewed as set mappings, and translation-invariant systems are uniquely characterized by special collections of input signals. Thi...

Title of dissertation: SPARSE SIGNAL REPRESENTATION IN DIGITAL AND BIOLOGICAL SYSTEMS Author: Matthew Guay, Doctor of Philosophy, 2016 Dissertation directed by: Professor Wojciech Czaja Department of Mathematics Theories of sparse signal representation, wherein a signal is decomposed as the sum of a small number of constituent elements, play increasing roles in both mathematical signal processi...

The pi calculus has been applied to modelling biochemical networks. In these applications, the modelling is done without considerations to exceptions. The Ipi calculus, the Interference pi calculus, is introduced to describe the signal transduction with aberrance. The calculus is obtained by adding two aberrant actions into the pi calculus and a tag system to check existing aberrance. A model o...

There is an ever-growing interest within the fields of neurophysiology—as well as within coding theory and signal processing—into the particular information transmission method employed by most neurons: spikes. Many models used today regard those voltage pulses as uniform events where only the occurrence of an event from a particular neuron at a particular moment in time matters. This signal re...

Perceptual image distortion measures can play a fundamental role in evaluating and optimizing imaging systems and image processing algorithms. Many existing measures are formulated to represent “just noticeable differences” (JNDs), as measured in psychophysical experiments on human subjects. But some image distortions, such as those arising from small changes in the intensity of the ambient ill...

Collerton et al.’s Perception and Attention Deficit (PAD) model argues that all recurrent complex visual hallucinations (RCVH) result from maladaptive, deficient sensory and attentional processing. We outline a constructivist-based representation of perception using signal detection theory, in which hallucinations are modeled as false alarms when confirmational perceptual information is lacking...

Multiresolution representations are very effective for analyzing the information content of images. We study the properties of the operator which approximates a signal at a given resolution. We show that the difference of information between the approximation of a signal at the resolutions 2’ + ’ and 2jcan be extracted by decomposing this signal on a wavelet orthonormal basis of L*(R”). In LL(R...

1 Laboratoire Images, Signaux et Systémes Intelligents (LISSI-E.A.3956), Université Paris Est Créteil Val de Marne, France 2Laboratoire d’Analyse, Numérique et d’Informatique (LANI), Universite Gaston Berger (UGB), Saint-Louis BP 234, Senegal 3 Ecole Polytechnique de Thiès, Thiès BP A10, Senegal 4Département de Mathématique et Informatique, Faculté des Scinces et Technique, Université Cheikh An...