Reduced Complexity Interpolation for
نویسندگان
چکیده
منابع مشابه
Presentation of K Nearest Neighbor Gaussian Interpolation and comparing it with Fuzzy Interpolation in Speech Recognition
Hidden Markov Model is a popular statisical method that is used in continious and discrete speech recognition. The probability density function of observation vectors in each state is estimated with discrete density or continious density modeling. The performance (in correct word recognition rate) of continious density is higher than discrete density HMM, but its computation complexity is very ...
متن کاملPresentation of K Nearest Neighbor Gaussian Interpolation and comparing it with Fuzzy Interpolation in Speech Recognition
Hidden Markov Model is a popular statisical method that is used in continious and discrete speech recognition. The probability density function of observation vectors in each state is estimated with discrete density or continious density modeling. The performance (in correct word recognition rate) of continious density is higher than discrete density HMM, but its computation complexity is very ...
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The waveform interpolation (WI) speech coding presents a good performance at low bit rate. However, the algorithm has a very high complexity in computation. In this paper, a low-complexity improved waveform interpolation speech coder at 2kbps is proposed. The improved coding scheme has greatly reduced the computational complexity and improved the reconstructed speech quality by using various te...
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The main computational steps in algebraic soft-decoding, as well as Sudan-type list-decoding, of ReedSolomon codes are interpolation and factorization. A series of transformations is given for the interpolation problem that arises in these decoding algorithms. These transformations reduce the space and time complexity to a small fraction of the complexity of the original interpolation problem. ...
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To estimate the channel frequency response in multicarrier systems, two new reduced complexity methods are proposed. While the first performs a minimum mean square error estimate using FFT’s, the latter performs a polynomial interpolation directly in the frequency domain. Simulation results are shown for a wideband indoor wireless channel.
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تاریخ انتشار 2007