Wavelets in a problem of signal processing

In this work a new method is proposed for noise reduction in speech signals in the wavelet domain. The method for signal processing makes use of a transfer function, obtained as a polynomial combination of three processings, denominated operators. The proposed method has the objective of overcoming the deficiencies of the thresholding methods and the effective processing of speech corrupted by real noises. Using the method, two speech signals are processed, contaminated by white noise and colored noises. To verify the quality of the processed signals, two evaluation measures are used: signal to noise ratio (SNR) and perceptual evaluation of speech quality (PESQ).

Transcription profiling of signal transduction-related genes in sugarcane tissues

A collection of 237,954 sugarcane ESTs was examined in search of signal transduction genes. Over 3,500 components involved in several aspects of signal transduction, transcription, development, cell cycle, stress responses and pathogen interaction were compiled into the Sugarcane Signal Transduction (SUCAST) Catalogue. Sequence comparisons and protein domain analysis revealed 477 receptors, 510 protein kinases, 107 protein phosphatases, 75 small GTPases, 17 G-proteins, 114 calcium and inositol metabolism proteins, and over 600 transcription factors. The elements were distributed into 29 main categories subdivided into 409 sub-categories. Genes with no matches in the public databases and of unknown function were also catalogued. A cDNA microarray was constructed to profile individual variation of plants cultivated in the field and transcript abundance in six plant organs (flowers, roots, leaves, lateral buds, and 1(st) and 4(th) internodes). From 1280 distinct elements analyzed, 217 (17%) presented differential expression in two biological samples of at least one of the tissues tested. A total of 153 genes (12%) presented highly similar expression levels in all tissues. A virtual profile matrix was constructed and the expression profiles were validated by real-time PCR. The expression data presented can aid in assigning function for the sugarcane genes and be useful for promoter characterization of this and other economically important grasses.

Control of thermal damage in grinding by digital signal processing of raw acoustic emission

Grinding process is usually the last finishing process of a precision component in the manufacturing industries. This process is utilized for manufacturing parts of different materials, so it demands results such as low roughness, dimensional and shape error control, optimum tool-life, with minimum cost and time. Damages on the parts are very expensive since the previous processes and the grinding itself are useless when the part is damaged in this stage. This work aims to investigate the efficiency of digital signal processing tools of acoustic emission signals in order to detect thermal damages in grinding process. To accomplish such a goal, an experimental work was carried out for 15 runs in a surface grinding machine operating with an aluminum oxide grinding wheel and ABNT 1045 e VC131 steels. The acoustic emission signals were acquired from a fixed sensor placed on the workpiece holder. A high sampling rate acquisition system at 2.5 MHz was used to collect the raw acoustic emission instead of root mean square value usually employed. In each test AE data was analyzed off-line, with results compared to inspection of each workpiece for burn and other metallurgical anomaly. A number of statistical signal processing tools have been evaluated.

A current-mode based Field-Programmable Analog Array for signal processing applications

This paper presents a new approach to develop Field Programmable Analog Arrays (FPAAs),(1) which avoids excessive number of programming elements in the signal path, thus enhancing the performance. The paper also introduces a novel FPAA architecture, devoid of the conventional switching and connection modules. The proposed FPAA is based on simple current mode sub-circuits. An uncompounded methodology has been employed for the programming of the Configurable Analog Cell (CAC). Current mode approach has enabled the operation of the FPAA presented here, over almost three decades of frequency range. We have demonstrated the feasibility of the FPAA by implementing some signal processing functions.

Experimental aspects of biomass fuels in a bubbling fluidized bed combustor

This work presents experimental information relevant to the combustion of biomass in a bubbling fluidized bed. The biomass distribution in a fluidized bed was studied through tests performed in a cold bed, while the volatiles released in the biomass pyrolysis, the burning rate of the resulting charcoal, and the combustion control regime, were studied through tests performed in a high temperature bed.Visual examination of photographs taken from a transparent walls bed, with a rectangular cross-section, showed that the large fuel particles, typical of biomass processing, were distributed in the bubbles, in the splash zone, and in the emulsion phase. The occurrence of biomass in the emulsion phase was favored by burning biomass particles of greater density and smaller size-expetimentally determined in each case. Decreasing the fuel particle size improved the biomass distribution inside the bed. The same was accomplished by increasing the superficial gas velocity as high as possible, compatibly with the acceptable elutriation.Burning tests showed that the biomass fuels have the advantage of reaching the diffusional regime at temperatures that can be lower than 1000 K, which ensures that the biomass fuels burn in a stable regime. (C) 2007 Elsevier B.V. All rights reserved.

Pattern recognition theory in nonlinear signal processing

A body of research has developed within the context of nonlinear signal and image processing that deals with the automatic, statistical design of digital window-based filters. Based on pairs of ideal and observed signals, a filter is designed in an effort to minimize the error between the ideal and filtered signals. The goodness of an optimal filter depends on the relation between the ideal and observed signals, but the goodness of a designed filter also depends on the amount of sample data from which it is designed. In order to lessen the design cost, a filter is often chosen from a given class of filters, thereby constraining the optimization and increasing the error of the optimal filter. To a great extent, the problem of filter design concerns striking the correct balance between the degree of constraint and the design cost. From a different perspective and in a different context, the problem of constraint versus sample size has been a major focus of study within the theory of pattern recognition. This paper discusses the design problem for nonlinear signal processing, shows how the issue naturally transitions into pattern recognition, and then provides a review of salient related pattern-recognition theory. In particular, it discusses classification rules, constrained classification, the Vapnik-Chervonenkis theory, and implications of that theory for morphological classifiers and neural networks. The paper closes by discussing some design approaches developed for nonlinear signal processing, and how the nature of these naturally lead to a decomposition of the error of a designed filter into a sum of the following components: the Bayes error of the unconstrained optimal filter, the cost of constraint, the cost of reducing complexity by compressing the original signal distribution, the design cost, and the contribution of prior knowledge to a decrease in the error. The main purpose of the paper is to present fundamental principles of pattern recognition theory within the framework of active research in nonlinear signal processing.

Hydrodynamic aspects of the amorphous alloy ribbon fabrication

Conditions for as-quenched amorphous ribbon fabrication by a single roll-casting method are analyzed from a hydrodynamic standpoint. The analysis is based on the investigation of the processing conditions for Fe 4 0Ni 40P 14B 6 amorphous ribbons. It is shown that the dependence of ribbon thickness on the ejection pressure for different roll angular velocities and different dimensions of crucible and orifice can be obtained from general considerations on the melt flow regime.

Neurophysiological aspects of musical auditory stimulation on cardiovascular system

Introduction: The literature has shown that musical stimulation can influence the cardiovascular system, however, the neurophysiological aspects of this influence are not yet fully elucidated. Objective: This study describes the influence of music on the neurophysiological mechanisms in the human body, specifically the variable blood pressure, as well as the neural mechanisms of music processing. Methods: Searches were conducted in Medline, PEDro, Lilacs and SciELO using the intersection of the keyword “music” with the keyword descriptors “blood pressure” and “neurophysiology”. Results: There were selected 11 articles, which indicated that music interferes in some aspects of physiological variables. Conclusion: Studies have indicated that music interferes on the control of blood pressure, heart and respiratory rate, through possible involvement of limbic brain areas which modulate hypothalamic-pituitary functions. Further studies are needed in order to identify the mechanisms by which this influence occurs.