FPGA-based link layer chip S19202 configuration
标签: configuration FPGA-based S19202 layer
上传时间: 2013-12-27
上传用户:z1191176801
MultiBand OFDM Physical Layer Proposal
标签: MultiBand Physical Proposal Layer
上传时间: 2013-12-27
上传用户:天诚24
iMX21 SDHC driver(PDD layer)
上传时间: 2013-12-19
上传用户:waitingfy
YAMAHA YMU762 IC MA-3 Sound Middleware sample source code , Include device driver , Operation API
标签: Middleware Operation Include YAMAHA
上传时间: 2014-01-08
上传用户:wanqunsheng
以太网物理层接口器件-10/100 Mbps Fast Ethernet Physical Layer TX/FX Single Chip Transceiver
标签: Transceiver Ethernet Physical Single
上传时间: 2016-10-13
上传用户:jackgao
this an example showing how the threading policy work ! It is the topic of the middleware. This program involves CORBA also.
标签: the middleware threading example
上传时间: 2013-11-30
上传用户:sqq
how to use the bluetooth module in the HCI layer
标签: bluetooth the module layer
上传时间: 2013-11-25
上传用户:yzy6007
文件操作系统(UcosII) File system s OS Layer file
上传时间: 2016-12-12
上传用户:1109003457
% Train a two layer neural network with the Levenberg-Marquardt % method. % % If desired, it is possible to use regularization by % weight decay. Also pruned (ie. not fully connected) networks can % be trained. % % Given a set of corresponding input-output pairs and an initial % network, % [W1,W2,critvec,iteration,lambda]=marq(NetDef,W1,W2,PHI,Y,trparms) % trains the network with the Levenberg-Marquardt method. % % The activation functions can be either linear or tanh. The % network architecture is defined by the matrix NetDef which % has two rows. The first row specifies the hidden layer and the % second row specifies the output layer.
标签: Levenberg-Marquardt desired network neural
上传时间: 2016-12-27
上传用户:jcljkh
Train a two layer neural network with a recursive prediction error % algorithm ("recursive Gauss-Newton"). Also pruned (i.e., not fully % connected) networks can be trained. % % The activation functions can either be linear or tanh. The network % architecture is defined by the matrix NetDef , which has of two % rows. The first row specifies the hidden layer while the second % specifies the output layer.
标签: recursive prediction algorithm Gauss-Ne
上传时间: 2016-12-27
上传用户:ljt101007