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TDNN1

于 2021-03-21 发布文件大小:470KB

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下载积分: 1 下载次数: 187

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代码说明：

Speech Recognition with TDNN(Time delay neural network)

文件列表：

TDNN1
.....\1.wav,88326,2009-02-17
.....\10.wav,88326,2009-02-17
.....\1th.wav,88388,2009-02-17
.....\2.wav,88326,2009-02-17
.....\2th.wav,88388,2009-02-17
.....\3.wav,88326,2009-02-17
.....\3th.wav,88388,2009-02-17
.....\4.wav,88326,2009-02-17
.....\4th.wav,88388,2009-02-17
.....\5.wav,88326,2009-02-17
.....\5th.wav,88388,2009-02-17
.....\6.wav,88326,2009-02-17
.....\7.wav,88326,2009-02-17
.....\8.wav,88326,2009-02-17
.....\9.wav,88326,2009-02-17
.....\framing.m,267,2010-06-19
.....\Minput.m,127,2010-06-19
.....\nl.m,74,2010-06-18
.....\RecogSound.m,1326,2010-06-19
.....\TDNN.asv,2125,2010-06-19
.....\TDNN.m,2178,2010-06-21

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bipso
围绕粒子群的当前质心对粒子群重新初始化.这样，每个粒子在随后的迭代中将在新的位置带着粒子在上次搜索中获得的“运动惯性”（wvi）向Pi，Pg的方向前进，从而可以在粒子群的运动过程中获得新的位置，增加求得更优解的机会.随着迭代的继续，经过变异的粒子群又将趋向于同一点，当粒子群收敛到一定程度时又进行下一次变异，如此反复，直到迭代结束.(particle swarm around the center of mass of the current PSO reinitialization. Thus, Each particle in the next iteration will be in the new location with particles in the last search was the "inertia" (wvi ) Pi, Pg orientation, and thus can PSO course of the campaign was a new position, increase seek better solutions opportunities. With the continued iteration, after variation of PSO will tend to the same point. When PSO converge to a certain extent when the next variation, so repeatedly, until the end of iteration.)

2006-08-19 17:39:33下载

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实现FASTICA算法，可以将高维数据映射到二维坐标上！(Achieve FASTICA algorithm can be high-dimensional data is mapped to the two-dimensional coordinate!)

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基本的分类，预测，回归等算法，适合初学者学习，配有注释，容易理解(Basic classification, prediction, regression algorithm, suitable for beginners to learn, with comments, easy to understand)

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This is the Graphical User Interface for performing Digital Modulation like ASK,PSK and FSK.This project can be extended for further digital modulation techniques.

2015-04-07 23:16:06下载

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语音识别中的模型和算法：动态时间归正技术（DTW），隐马尔可夫模型（HMM），高斯混合模型（GMM），高斯混合模型（GMM）(Speech Recognition model and algorithms : dynamic time Reformed technology (DTW) Hidden Markov Model (HMM), Gaussian mixture model (GMM), Gaussian mixture model (GMM))

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实现快速贝叶斯算法,先验超参数分布不再使用高斯函数而是用拉普拉斯函数代替(Fast Bayesian algorithm, a priori super-Gaussian parameter distribution is no longer used but with the Laplace function instead)

2013-10-13 13:49:34下载

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积分：1

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TDNN1

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