genomic signal processing is a relatively new field in bioinformatics, in which signal processing algorithms and methods are used to study functional structures in the dna. an appropriate mapping of the dna sequence into one or more numerical sequences enables the use of many digital signal processing tools in the analysis of different genomic sequences. also, a novel influenza a (h1n1) virus o...

Dual Nonlinear Correlation (DNC) is a general operation in optical pattern recognition where the nonlinear pre-processing introduced in the reference channel may differ from that introduced in the input channel. It involves a number of popular linear and nonlinear filtering methods and can be implemented by an optoelectronic two-step joint transform correlator (JTC). The eventual capabilities o...

The Dual Nonlinear Correlation (DNC) model implemented by an optoelectronic joint transform correlator (JTC) (Millán et al., Dual Nonlinear Correlation in Optical Pattern Recognition I, Óptica Pura y Aplicada 38, núm. 2, 75-83, 2005) provides a pattern recognition system with adjustable discrimination capability (DC). By varying the values of two real parameters (L and M) in the DNC we obtain e...

This paper argues that neural networks are good vehicles for automatic speech recognition not simply because they provide non-linear pattern recognition but because their architecture allows the incorporation and exploitation of existing knowledge about speech. The paper is in two parts: Part I defends the need for the incorporation of existing knowledge, while Part II sketches a speech recogni...

This book is aimed at researchers with backgrounds in dynamic systems and control and for use in an advanced graduate-level course. The main subjects cover knowledge acquisition, representation, and utilization in unknown nonlinear dynamic processes using a deterministic framework. This model of information processing, known as deterministic learning, is developed and used for problems of nonli...

the nonlinear static procedures (nsps) proposed by design codes do not lead to reliable results especially for tall buildings. they generally provide inconsistent estimates of inelastic seismic demands, especially for the top floors due to their inabilities in considering the higher modes effects. in this paper, a new enhanced pushover procedure is proposed which is based on the envelope of the...

most contemporary clinical reasoning tests typically assess non-automatic thinking. therefore, a test is needed to measure automatic reasoning or pattern recognition, which has been largely neglected in clinical reasoning tests. the puzzle test (pt) is dedicated to assess automatic clinical reasoning in routine situations. this test has been introduced first in 2009 by monajemi et al in the oly...

in this research, an iterative approach is employed to recognize and classify control chart patterns. to do this, by taking new observations on the quality characteristic under consideration, the maximum likelihood estimator of pattern parameters is first obtained and then the probability of each pattern is determined. then using bayes’ rule, probabilities are updated recursively. finally, when...

An attractor modeling algorithm is introduced which draws upon techniques found in nonlineax dynamics and pattern recognition. The technique is motivated. by the need for quantitative measures that are able to assess the stability of biological neural networks which utilize nonlinear dynamics to process information. Attractor Density Models with Application to Analyzing the Stability of Biologi...