In this contribution a modified scheme for linear prediction analysis is presented which controls the degree of decorrelation by a parameter α. In consideration of this parameter the signal to noise ratio of a linear predictive coding scheme is investigated and finally maximized for open loop quantization. Also, the new parameter can be used to control the spectral shape of the quantization err...

Introduction In order to improve the quality of life of amputees, biomechatronic researchers and biomedical engineers have been trying to use a combination of various techniques to provide suitable rehabilitation systems. Diverse biomedical signals, acquired from a specialized organ or cell system, e.g., the nervous system, are the driving force for the whole system. Electromyography(EMG), as a...

For wideband speech signal, if traditional noise cancelation algorithms are adjusted, it can be operated wrong way since unvoiced speech is similar as white Gaussian noise and high frequency on voiced speech that is over than MVF is also similar as noise in the presence of noise circumstance. So when speech signal is damaged by these reasons, it cannot be recognized exactly because that each ph...

This paper suggests a novel methodology for building robust information processing systems based on wavelet and neural network methods to be used in decision making tasks when image information is involved as well as in prediction and modelling tasks when signal information should be processed. It is proposed that the efficiency of such systems is increased when they simultaneously process inpu...

Multihypothesis motion-compensating predictors combine several motion-compensated signals to predict the current frame signal. More than one motion-compensated signal, or hypothesis, is selected for transmission. Long-term memory motion-compensated prediction is a further concept for efficient video compression and is an example for forward-adaptive hypothesis switching. One motion-compensated ...

Heart diseases are common these days due to unhealthy food habits. One of the biggest causes of deaths today is heart diseases. These need to be monitored and diagnosed early to shun deaths because of coronary heart diseases. ECG signal i.e. Electrocardiogram signal is used to detect the heart disease, an individual is suffering from. The ECG signal formed will let the doctor know about the hea...

Background: Reinforcement learning models now play a central role in modern attempts to understand how the brain categorizes and values events traditionally framed by psychology as rewards and punishments. These models provide a way to design and interpret of reward expectancy experiments in humans across a wide range of rewarding dimensions. They also provide a connection to computational mode...

UNLABELLED The accuracy of current signal peptide predictors is outstanding. The most successful predictors are based on neural networks and hidden Markov models, reaching a sensitivity of 99% and an accuracy of 95%. Here, we demonstrate that the popular BLASTP alignment tool can be tuned for signal peptide prediction reaching the same high level of prediction success. Alignment-based technique...

In this paper, we propose a new method of processing speech degraded by reverberation. The method is based on analysis of short (2 ms) segments of data to enhance the regions in the speech signal having high signal-to-reverberant component ratio (SRR). The short segment analysis shows that SRR is different in different segments of speech. The processing method involves identifying and manipulat...

Due to the ever increasing complexity of wireless network design, wireless network simulation engines have become a necessary tool for wireless network engineers. A signal-strength prediction system lies at the foundation of every wireless simulator, making signal-strength prediction for microcells and picocells an important research topic in the radio field. Efficient and accurate methods are ...