Background: Electromyographic (EMG) signal decomposition is the process by which an EMG signal is decomposed into its constituent motor unit potential trains (MUPTs). A major step in EMG decomposition is feature extraction in which each detected motor unit potential (MUP) is represented by a feature vector. As with any other pattern recognition system, feature extraction has a significant impac...

background: electromyographic (emg) signal decomposition is the process by which an emg signal is decomposed into its constituent motor unit potential trains (mupts). a major step in emg decomposition is feature extraction in which each detected motor unit potential (mup) is represented by a feature vector. as with any other pattern recognition system, feature extraction has a significant impac...

A new method based on principal component analysis (PCA) and artificial neural networks (ANN) is proposed for fault diagnosis of gearboxes. Firstly the six different base wavelets are considered, in which three are from real valued and other three from complex valued. Two wavelet selection criteria Maximum Energy to Shannon Entropy ratio and Maximum Relative Wavelet Energy are used and compared...

Introduction: Visual evoked potentials contain certain diagnostic information which have proved to be of importance in the visual systems functional integrity. Due to substantial decrease of amplitude in extra macular stimulation in commonly used pattern VEPs, differentiating normal and abnormal signals can prove to be quite an obstacle. Due to developments of use of machine l...

as the t-wave section in electrocardiogram (ecg) illustrates the repolarisation phase of heart activity, the information which is accumulated in this section is so significant that can explain the proper operation of electrical activities in heart. long qt syndrome (lqt) and t-wave alternans (twa) have imperceptible effects on time and amplitude of t-wave interval. therefore, t-wave shapes of t...

Image registration is a crucial step in most image processing tasks for which the final result is achieved from a combination of various resources. In general, the majority of registration methods consist of the following four steps: feature extraction, feature matching, transform modeling, and finally image resampling. As the accuracy of a registration process is highly dependent to the fe...

in the current iris recognition systems, noise removing step is only used to detect noisy parts of the iris region and features extracted from there will be excluded in matching step. whereas depending on the filter structure used in feature extraction, the noisy parts may influence relevant features. to the best of our knowledge, the effect of noise factors on feature extraction has not been c...

A standout amongst the most effective strategies for bosom malignancy early discovery is mammography. Another strategy for identification and arrangement of miniaturized scale calcifications is displayed. It should be possible in four phases: in the first place, pre processing stage manages clamour expulsion, and standardized the picture. Second stage, K-Means bunching (KMC) is utilized for div...

A standout amongst the most effective strategies for bosom malignancy early discovery is mammography. Another strategy for identification and arrangement of miniaturized scale calcifications is displayed. It should be possible in four phases: in the first place, pre processing stage manages clamour expulsion, and standardized the picture. Second stage, K-Means bunching (KMC) is utilized for div...