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DNN_toolbox

于 2020-11-06 发布 文件大小:78029KB
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  语音分离用的深度神经网络工具箱，matlab，非常全 (This folder contains Matlab programs for a toolbox for supervised speech separation using deep neural networks (DNNs).)

文件列表：

DNN_toolbox
...........\config
...........\......\list.txt,8640,2016-03-08
...........\......\list120.txt,1440,2016-03-08
...........\......\list120_short.txt,120,2016-03-08
...........\......\list600.txt,7200,2016-03-08
...........\......\list600_short.txt,120,2016-03-08
...........\DATA
...........\dnn
...........\...\main
...........\...\....\checkPerformanceOnData_no_print.m,423,2016-03-08
...........\...\....\checkPerformanceOnData_no_print_wiener.m,527,2016-03-08
...........\...\....\checkPerformanceOnData_save_IBM.m,3763,2016-03-08
...........\...\....\checkPerformanceOnData_save_wiener.m,3709,2016-03-08
...........\...\....\computeNetGradientNoRolling.m,1497,2016-03-08
...........\...\....\dnn_train.m,2356,2016-03-08
...........\...\....\forwardPass.m,1646,2016-03-08
...........\...\....\forwardPass_diff_drop_ratio.m,1433,2016-03-08
...........\...\....\funcDeepNetTrainNoRolling.m,4675,2016-03-08
...........\...\....\getOutputFromNet.m,806,2016-03-08
...........\...\....\getOutputFromNetSplit.m,585,2016-03-08
...........\...\....\stoi.m,7760,2016-03-08
...........\...\mvn_store.m,1764,2016-03-08
...........\...\pretraining
...........\...\...........\pretrainRBMStack.m,1084,2016-03-08
...........\...\...........\trainRBM.m,3150,2016-03-08
...........\...\run_every.m,1026,2016-03-08
...........\...\utility
...........\...\.......\batchComputeMeanStd.m,405,2016-03-08
...........\...\.......\compute_unit_activation.m,436,2016-03-08
...........\...\.......\compute_unit_gradient.m,414,2016-03-08
...........\...\.......\count_struct.m,188,2016-03-08
...........\...\.......\deltas.m,691,2016-03-08
...........\...\.......\format_print.m,321,2016-03-08
...........\...\.......\gather_net.m,178,2016-03-08
...........\...\.......\genBatchID.m,335,2016-03-08
...........\...\.......\getHITFA.m,217,2016-03-08
...........\...\.......\getMSE.m,82,2016-03-08
...........\...\.......\getNetParamStr.m,304,2016-03-08
...........\...\.......\initializeRandWSparse.m,374,2016-03-08
...........\...\.......\initRandW.m,111,2016-03-08
...........\...\.......\initRandWSparse.m,251,2016-03-08
...........\...\.......\make_labels.m,144,2016-03-08
...........\...\.......\make_window_buffer.m,328,2016-03-08
...........\...\.......\meanVarArmaNormalize_Test.m,177,2016-03-08
...........\...\.......\meanVarNormalize.m,244,2016-03-08
...........\...\.......\meanVarNormalize_Test.m,273,2016-03-08
...........\...\.......\mean_var_norm.m,620,2016-03-08
...........\...\.......\mean_var_norm_testing.m,279,2016-03-08
...........\...\.......\netRolling.m,396,2016-03-08
...........\...\.......\netUnRolling.m,124,2016-03-08
...........\...\.......\randInitNet.m,714,2016-03-08
...........\...\.......\randinitWbSparse.m,404,2016-03-08
...........\...\.......\relu.m,156,2016-03-08
...........\...\.......\relu_grad.m,43,2016-03-08
...........\...\.......\resyn
...........\...\.......\.....\cochleagram.m,1173,2016-03-08
...........\...\.......\.....\cochplot.m,1145,2016-03-08
...........\...\.......\.....\erb2hz.m,263,2016-03-08
...........\...\.......\.....\f_af_bf_cf.mat,1280,2016-03-08
...........\...\.......\.....\gammatone.m,1620,2016-03-08
...........\...\.......\.....\hz2erb.m,268,2016-03-08
...........\...\.......\.....\ibm.m,1685,2016-03-08
...........\...\.......\.....\loudness.m,1164,2016-03-08
...........\...\.......\.....\meddis.m,1681,2016-03-08
...........\...\.......\.....\synthesis.m,3265,2016-03-08
...........\...\.......\sigmoid.m,51,2016-03-08
...........\...\.......\sigmoid_grad.m,43,2016-03-08
...........\...\.......\softmax.m,143,2016-03-08
...........\...\.......\unroll_struct.m,296,2016-03-08
...........\...\.......\zeroInitNet.m,689,2016-03-08
...........\gen_mixture
...........\...........\generate_test_mix.m,2960,2016-03-08
...........\...........\generate_train_mix.m,3277,2016-03-08
...........\...........\get_all_noise_test.m,353,2016-03-08
...........\...........\get_all_noise_train.m,382,2016-03-08
...........\get_feat
...........\........\features
...........\........\........\ams
...........\........\........\...\AMS_init_FFT.m,1756,2016-03-08
...........\........\........\...\create_crit_filter.m,3875,2016-03-08
...........\........\........\...\env_extraction_gmt_chan2.m,346,2016-03-08
...........\........\........\...\extract_AMS_perChan.m,1975,2016-03-08
...........\........\........\...\get_amsfeature_chan_fast.m,338,2016-03-08
...........\........\........\...\mel.m,831,2016-03-08
...........\........\........\cochleagram
...........\........\........\...........\cochleagram.m,1173,2016-03-08
...........\........\........\...........\erb2hz.m,263,2016-03-08
...........\........\........\...........\f_af_bf_cf.mat,1280,2016-03-08
...........\........\........\...........\gammatone.m,1616,2016-03-08
...........\........\........\...........\hz2erb.m,268,2016-03-08
...........\........\........\...........\ibm.m,1685,2016-03-08
...........\........\........\...........\ideal.m,356,2016-03-08
...........\........\........\...........\loudness.m,1164,2016-03-08
...........\........\........\...........\meddis.m,1681,2016-03-08
...........\........\........\...........\synthesis.m,3265,2016-03-08
...........\........\........\...........\wiener.m,245,2016-03-08
...........\........\........\my_features_AmsRastaplpMfccGf.m,854,2016-03-08
...........\........\........\rastamat
...........\........\........\........\audspec.m,1266,2016-03-08

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  • tongxunyuanlishejibaogao
    数字信号处理的直接对象是数字信号，处理的方式是数值运算的方式，它涉及到的内容非常丰富和广泛，它是应用最快、成效最显著的新学科之一，做为信息专业的专业基础课，需要掌握其基本理论和基本的分析方法，通过理论和实践、原理和应用结合让学生掌握知识。而matlab是集数学计算、图形处理和程序语言设计于一体的软件，通过matlab来实现数字信号处理的有关表达，最终实现课程设计的目的。(Direct object of digital signal processing digital signal processing approach is the way value operation, which involves the contents of the very rich and extensive, it is the fastest application, the effectiveness of the most significant one of the new disciplines, as information on professional expertise basic course, need to understand the basic theory and basic methods of analysis, theory and practice, theory and application integration to enable students to acquire knowledge. The matlab is a mathematical calculation, graphics processing and program design in one of the software, through matlab to implement digital signal processing of the expression, and ultimately the purpose of course design.)
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