文件名称:haykin_NeuralNetwork_pdf_matlab_soure_code
- 所属分类:
- 人工智能/神经网络/遗传算法
- 资源属性:
- [Matlab] [源码]
- 上传时间:
- 2012-11-26
- 文件大小:
- 17.91mb
- 下载次数:
- 0次
- 提 供 者:
- k**
- 相关连接:
- 无
- 下载说明:
- 别用迅雷下载,失败请重下,重下不扣分!
介绍说明--下载内容均来自于网络,请自行研究使用
haykin的神经网络原理,包括pdf文件和书中附带的matlab源码-haykin of neural network theory, including pdf files and books with the matlab source
(系统自动生成,下载前可以参看下载内容)
下载文件列表
haykin神经网络原理_0\haykin\bpm_dec_bnds.m
....................\......\bpm_phi.m
....................\......\bpm_phi_d.m
....................\......\bpm_test.m
....................\......\bpm_train.m
....................\......\bsb.m
....................\......\colmult.m
....................\......\gha.m
....................\......\gha_chopstak.m
....................\......\gha_data.mat
....................\......\gha_dispwe.m
....................\......\gha_getcoeffs.m
....................\......\gha_getweights.m
....................\......\gha_intermed_res.mat
....................\......\gha_quantcoeffs.m
....................\......\gha_recompose.m
....................\......\gha_unchopst.m
....................\......\hop_data.mat
....................\......\hop_demo.m
....................\......\hop_flip.m
....................\......\hop_plotdig.m
....................\......\hop_plotpats.m
....................\......\hop_stor.m
....................\......\hop_test.m
....................\......\ica.m
....................\......\mk_data.m
....................\......\pim.m
....................\......\pl_circ.m
....................\......\rbf.m
....................\......\rbf_correct.m
....................\......\rbf_db.m
....................\......\rbf_mkGF.m
....................\......\rbf_test.m
....................\......\readme
....................\......\sgn.m
....................\......\shuffle.m
....................\......\som_1d.m
....................\......\som_2d.m
....................\......\som_2d_demo.m
....................\......\som_pl_map.m
....................\......\svm_dec_bnd.m
....................\......\svm_proymayor.m
....................\......\svm_proymenor.m
....................\......\svm_rbf.m
....................\......\svm_test.m
....................\......\thresh.m
....................\神经网络原理_0.pdf
....................\haykin
haykin神经网络原理_0
....................\......\bpm_phi.m
....................\......\bpm_phi_d.m
....................\......\bpm_test.m
....................\......\bpm_train.m
....................\......\bsb.m
....................\......\colmult.m
....................\......\gha.m
....................\......\gha_chopstak.m
....................\......\gha_data.mat
....................\......\gha_dispwe.m
....................\......\gha_getcoeffs.m
....................\......\gha_getweights.m
....................\......\gha_intermed_res.mat
....................\......\gha_quantcoeffs.m
....................\......\gha_recompose.m
....................\......\gha_unchopst.m
....................\......\hop_data.mat
....................\......\hop_demo.m
....................\......\hop_flip.m
....................\......\hop_plotdig.m
....................\......\hop_plotpats.m
....................\......\hop_stor.m
....................\......\hop_test.m
....................\......\ica.m
....................\......\mk_data.m
....................\......\pim.m
....................\......\pl_circ.m
....................\......\rbf.m
....................\......\rbf_correct.m
....................\......\rbf_db.m
....................\......\rbf_mkGF.m
....................\......\rbf_test.m
....................\......\readme
....................\......\sgn.m
....................\......\shuffle.m
....................\......\som_1d.m
....................\......\som_2d.m
....................\......\som_2d_demo.m
....................\......\som_pl_map.m
....................\......\svm_dec_bnd.m
....................\......\svm_proymayor.m
....................\......\svm_proymenor.m
....................\......\svm_rbf.m
....................\......\svm_test.m
....................\......\thresh.m
....................\神经网络原理_0.pdf
....................\haykin
haykin神经网络原理_0