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C. E. Pedreira, “Learning Vector Quantization with Training Data Selections,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 28, No. 1, 2006, pp. 157-162.

has been cited by the following article:

• TITLE: Fuzzy Voice Coding with Significant Impulses Modeling and Redundant Waveform Recycling

  AUTHORS: Ismael Rosas Arriaga, Juan C. García Infante, J. Carlos Sánchez García

  KEYWORDS: Coding; Signal Processing; Fuzzy Logic; Algorithms; Pattern Recognition

  JOURNAL NAME: Communications and Network, Vol.5 No.1, February 27, 2013

  ABSTRACT: This paper proposes a voice codification based on two algorithms that make the wave form codification in time domain. The first uses the significant impulse model (SIM), which has as a goal to operate as an endpoint detector and as a dawn sampling, through the detection and selection of the significant valleys and crests; the second algorithm, is a redundant wave-form recycler (RWR) that uses an architecture based on fuzzy logic with an accumulative memory. The fuzzy algorithm obtains the similitude grade between the redundant wave forms, this with the objective of save into an knowledge base the patterns, based on the no supervised learning and when there are into memory, automatically there will be used to identified their arrive respect to the input signal, substituting the input block by the correspondent pattern into memory. This decoding process is using the SIM interpolation with a memory in accordance to the RWR.