Signal Analysis and Pattern Identification
Digital-Signal-Type Identification Using an Efficient Identifier
... digital-signal-type identification techniques usually can be categorized in two main principles: the decision-theoretic (DT) and the pattern recognition ...careful analysis that are re- quired ...
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Using Sentiment Analysis and Pattern Matching to Signal User Review Abnormalities
... the analysis and pattern matching we ...sentiment analysis models we used were trained on the English language, and there was no way for them to distinguish users based on their nationality or ...
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Identification and Small-Signal Analysis of Interaction Modes in VSC MTDC Systems
... Fig. 15 depicts the relative participation of the different converters in the interaction modes. Comparison with Fig. 12 shows that the participation pattern of the interaction modes associated with the cables (A ...
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Identification of Noisy Utterance Speech Signal using GA Based Optimized 2D MFCC Method and a Bispectrum Analysis
... spectrum analysis method is usually used as a feature extraction in a speaker identification ...speech signal under harsh noise con- ditions, we have developed a speaker identification system ...
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How does the pitch and pattern of a signal affect auditory arousal thresholds?
... Hearing was screened with an Endomed SA 210/2 #13355. Polysomnographic sleep recordings were conducted with the Compumedics Siesta or Series E data acquisition system. A laptop computer was used to monitor sleep patterns ...
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Identification of Drosophila Genes Modulating Janus Kinase/Signal Transducer and Activator of Transcription Signal Transduction
... the identification of signal transduc- tion pathway components (D ickson et ...multiple signal transduction pathways including EGFR, Hh, Notch, Dpp, and ...
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Matching and fusing signal-estimation errors for similarity-based pattern classification
... The unknown signal is assigned to class i * if the average distortion measure of its LPC feature vector Xm and the LPC feature codebook C i is minimum, that is i* = argrninDxm, Ci , 52 [r] ...
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A NEW APPROACH FOR PATTERN RECOGNITION OF NON-STATIONARY SIGNAL USING FWNN
... and signal to noise improvements in the time ...power signal classification using FWNN (Fuzzy wavelet Neural Network) have been ...time analysis and Feature extraction from the Non-stationary power ...
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Identification of Tooth Damage in a Gearbox by Vibration Signal Analysis
... Gearbox is necessary for prime movers to transmit the power from one part to another. Gearbox contains many parts such as gear pairs, bearings, shafts, coupling etc., and each part has its own vibration characteristics ...
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Methylation pattern analysis in prostate cancer tissue: identification of biomarkers using an MS MLPA approach
... We performed a two-step MSP for RARB, RASSF1A, SCGB3A1 and CCND2 methylation analysis, as previ- ously described by Zhu et al. [22]. First, we performed a multiplex PCR using C1000 ™ Thermal Cycler (Biorad) ...
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Clinical Application of PCR Restriction Enzyme Pattern Analysis for Rapid Identification of Aerobic Actinomycete Isolates
... enzyme pattern analysis (PRA) for routine identification of aerobic actinomycete clinical isolates were evaluated for 299 cultures submitted to the Mycobacteria/Nocardia Laboratory at the University ...
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Phonocardiographic Signal and Electrocardiographic Signal Analysis for the Detection of Cardiovascular Diseases
... Feature Extraction and Feature Selection The third module deals with the extraction of features from the heart sound signal. The various time domain features and the frequency domain features are extracted. The ...
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Signal Identification Using a New High Efficient Technique
... automatic signal type ...packet analysis (WPA) as a feature extractor and a multiplayer perceptron (MLP) neural network that applies back-propagation (BP) with momentum and adaptive learning ...for ...
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Analysis of landscape pattern based on the point pattern method
... Point Patterns Analysis: Point patterns can be studied by the order analysis [13]. One of the most commonly used order methods is Ripley’s K function, which is a tool for analyzing completely mapped spatial ...
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Nonlinear Analysis of the BOLD Signal
... The initial eight scans were discarded to avoid magnetic saturation e ff ects. The remaining images were realigned and corrected for movement-related e ff ects within SPM (Wellcome Department of Cognitive Neurology, ...
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Large-Signal Network Analysis
... • 1994 harmonic phase calibration with a characterized SRD, traceable to a nose-to-nose calibrated sampling oscilloscope (Verspecht).. • 2000 IF calibration (Verspecht).[r] ...
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Statistical Approaches for Signal Processing with Application to Automatic Singer Identification
... the pattern recognition classifier most widely used in speaker recognition system due to its capability of representing a large class of sample distribution ([Huang et ...
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Brain Signal Analysis in Alcoholism
... The FLANN was first purposed by Pao [4] is a single layered artificial neural network structure capable of performing complex decision region by generating non-linear decision boundary. The FLANN can be used for function ...
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Artificial Interaction Pattern Identification using Eabc Algorithm
... Coginitive Model Based Emotion Recognition From Facial Expressions For Live Human Computer Interaction saysThe goal of this paper is to design a model with the capability of classifying the uncertainty, contradiction and ...
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