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).

Aspects of signal transduction in the gastrointestinal tract

This study was undertaken to increase knowledge of the mechanisms of inter- and intracellular signalling in the gastrointestinal tract. Specific aims were: to use cell lines to elucidate factors affecting growth of gastric cells, to investigate the distribution and aspects of function of isoforms of protein kinase C in a gastric cell line and in the rat gastrointestinal tract and to determine the presence and regulation of nitric oxide synthase in gastrointestinal tissues from the rat and in cell lines. The gastric cancer cell line HGT-1 was used to investigate control of growth. Increases in cell number were found to be dependent on the seeding density of the cells. In cells plated at low density insulin, epidermal growth factor and gastrin all increased cell number. Gastrin produced a bell-shaped dose response curve with a maximum activity at 5nM. No effect of gastrin was apparent in cells plated at high density. α and β isoforms of protein kinase C were found, by immunoblotting procedures, to be widespread in the gastrointestinal tract of the rat, but protein kinase Cε was confined to the gastric mucosa and gastrointestinal smooth muscle. HGT-1 cells contained protein kinase C α and ε but β or γ were not detected. Preincubation of HGT-1 cells for 24h with 1μM phorbol-12,13-dibutyrate down-regulated protein kinase C α but not ε. The inhibition by the activator of protein kinase C, 12-O-tetradecanoylphorbol 13-acetate (TPA) of the histamine-stimulated increase in cAMP in HGT-1 cells was down regulated by phorbol-12,13-dibutyrate. Inhibition of histamine-stimulation of adenylate cyclase by TPA was Ca2+-dependent and inhibited by the addition of an antibody to protein kinase C α. A role for protein kinase C α in modulating the effect of histamine on adenylate cyclase in HGT-1 cells is suggested. No nitric oxide synthase activity was detected in the gastrointestinal cell lines HGT-l, MKN-45 or CaCo-2. Ca2+-dependent nitric oxide synthase activity was observed in the gastric mucosa and the gastrointestinal smooth muscle from stomach to colon. The gastric: mucosal enzyme was soluble and showed half-maximal activity at 400nM Ca2+. Pretreatment of rats with endotoxin (3mg/kg body weight) induced nitric oxide synthase activity in both jejunal, ileal and colonic mucosa and muscle. A major portion of the induced activity in ileal and colonic mucosa was Ca2+-independent. Nitric oxide synthase activity in a high-density fraction of gastric mucosal cells was inhibited in a dose-dependent fashion by L-nitroarginine, NG-monomethyl-L-arginine, trifluoperazine and L-canavanine (in descending order of potency). Preincubation with okadaic acid and addition of ATPlMg2+ to the homogenisation buffer inhibited enzyme activity, which implies that phosphorylation inhibits gastric mucosal nitric oxide synthase.

Compensatory signal processing for profoundly hearing-impaired listeners: the transmission of fundamental frequency

This paper reviews a study to determine the usefulness of signal processing along with lipreading in improving speech perception of profoundly hearing impaired persons.

Signal processing of physiological signals for automated assessment of stress in computer users

The need to provide computers with the ability to distinguish the affective state of their users is a major requirement for the practical implementation of affective computing concepts. This dissertation proposes the application of signal processing methods on physiological signals to extract from them features that can be processed by learning pattern recognition systems to provide cues about a person's affective state. In particular, combining physiological information sensed from a user's left hand in a non-invasive way with the pupil diameter information from an eye-tracking system may provide a computer with an awareness of its user's affective responses in the course of human-computer interactions. In this study an integrated hardware-software setup was developed to achieve automatic assessment of the affective status of a computer user. A computer-based "Paced Stroop Test" was designed as a stimulus to elicit emotional stress in the subject during the experiment. Four signals: the Galvanic Skin Response (GSR), the Blood Volume Pulse (BVP), the Skin Temperature (ST) and the Pupil Diameter (PD), were monitored and analyzed to differentiate affective states in the user. Several signal processing techniques were applied on the collected signals to extract their most relevant features. These features were analyzed with learning classification systems, to accomplish the affective state identification. Three learning algorithms: Naïve Bayes, Decision Tree and Support Vector Machine were applied to this identification process and their levels of classification accuracy were compared. The results achieved indicate that the physiological signals monitored do, in fact, have a strong correlation with the changes in the emotional states of the experimental subjects. These results also revealed that the inclusion of pupil diameter information significantly improved the performance of the emotion recognition system. ^

High signal to noise ratio THz spectroscopy with ASOPS and signal processing schemes for mapping and controlling molecular and bulk relaxation processes

Asynchronous Optical Sampling has the potential to improve signal to noise ratio in THz transient sperctrometry. The design of an inexpensive control scheme for synchronising two femtosecond pulse frequency comb generators at an offset frequency of 20 kHz is discussed. The suitability of a range of signal processing schemes adopted from the Systems Identification and Control Theory community for further processing recorded THz transients in the time and frequency domain are outlined. Finally, possibilities for femtosecond pulse shaping using genetic algorithms are mentioned.

Signal Processing and patternrecognition algorithm for monitoringParkinson’s disease.

This masters thesis describes the development of signal processing and patternrecognition in monitoring Parkison’s disease. It involves the development of a signalprocess algorithm and passing it into a pattern recogniton algorithm also. Thesealgorithms are used to determine , predict and make a conclusion on the study ofparkison’s disease. We get to understand the nature of how the parkinson’s disease isin humans.

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.

Fault detection in rotating machines by vibration signal processing techniques

Machines with moving parts give rise to vibrations and consequently noise. The setting up and the status of each machine yield to a peculiar vibration signature. Therefore, a change in the vibration signature, due to a change in the machine state, can be used to detect incipient defects before they become critical. This is the goal of condition monitoring, in which the informations obtained from a machine signature are used in order to detect faults at an early stage. There are a large number of signal processing techniques that can be used in order to extract interesting information from a measured vibration signal. This study seeks to detect rotating machine defects using a range of techniques including synchronous time averaging, Hilbert transform-based demodulation, continuous wavelet transform, Wigner-Ville distribution and spectral correlation density function. The detection and the diagnostic capability of these techniques are discussed and compared on the basis of experimental results concerning gear tooth faults, i.e. fatigue crack at the tooth root and tooth spalls of different sizes, as well as assembly faults in diesel engine. Moreover, the sensitivity to fault severity is assessed by the application of these signal processing techniques to gear tooth faults of different sizes.

Cultured neural networks

This special section contains papers addressing various aspects associated with the issue Of Cultured neural networks. These are networks, that are formed through the monitored growth of biological neural tissue. In keeping with the aims of the International Journal of Adaptive Control and Signal Processing, the key focus of these papers is to took at particular aspects of signal processing in terms of both stimulating such a network and in assigning intent to signals collected as network outputs. Copyright (C) 2009 John Wiley & Sons, Ltd.