Artificial neural network (ANN) has application in communication engineering in diverse areas such as channel equalization, channel modeling, error control code because of its capability of nonlinear processing, adaptability, and parallel processing. On the other hand, wavelet transform (WT) with both the time and the frequency resolution provides the exact representation of signal in both doma...

In this paper, application of sparse representation (factorization) of signals over an overcomplete basis (dictionary) for signal classification is discussed. Searching for the sparse representation of a signal over an overcomplete dictionary is achieved by optimizing an objective function that includes two terms: one that measures the signal reconstruction error and another that measures the s...

This paper gives an overview of one of the most important features in our synthesis language called PWGLSynth. We will concentrate on how to represent visually multichannel signals in a synthesis patch. PWGLSynth synthesis boxes support vectored inputs and outputs. This scheme is useful as it allows to construct compound entities which are used often in sound synthesis such as banks, parallel s...