％ 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.
標(biāo)簽： Levenberg-Marquardt desired network neural
上傳時(shí)間： 2016-12-27
上傳用戶：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.
標(biāo)簽： recursive prediction algorithm Gauss-Ne
上傳時(shí)間： 2016-12-27
上傳用戶：ljt101007
Java is the first language to provide a cross-platform I/O library that is powerful enough to handle all these diverse tasks. Java is the first programming language with a modern, object-oriented approach to input and output. Java s I/O model is more powerful and more suited to real-world tasks than any other major language used today. Java I/O is the first and still the only book to fully expose the power and sophistication of this library.
標(biāo)簽： cross-platform language powerful provide
上傳時(shí)間： 2014-01-07
上傳用戶：pompey
數(shù)值計(jì)算牛頓迭代法的matlab源程序 說(shuō)明如下： ％fun----input,the part as the form of f(x) in the equation f(x)=0 ％ ini----input,sets the starting point to ini ％ err----input,sets admissible error ％ sol----output,returns the root of equation
標(biāo)簽： the equation matlab input
上傳時(shí)間： 2014-01-12
上傳用戶：妄想演繹師
數(shù)值分析高斯——列主元消去法主程序 說(shuō)明如下： ％ a----input,matrix of coefficient ％ b----input,right vector ％ sol----output,returns the solution of linear equation
標(biāo)簽： input coefficient matrix vector
上傳時(shí)間： 2017-01-01
上傳用戶：dancnc
Overview Input Clock = 24Mhz Preview VGA 15fps @ 60Hz VGA 12.5fps @ 50Hz Capture VGA 15fps @ 60Hz VGA 12.5fps @ 50Hz Output Format YCbCr 4:2:2 (ITU 656) YCbCr to RGB conversion R = Y + (351*(Cr – 128)) >> 8 G = Y – (179*(Cr – 128) + 86*(Cb – 128))>>8 B = Y + (443*(Cb – 128)) >> 8
標(biāo)簽： VGA fps Overview Capture
上傳時(shí)間： 2013-12-24
上傳用戶：遠(yuǎn)遠(yuǎn)ssad
本例展示了如何利用外設(shè)TIM2來(lái)產(chǎn)生四路頻率不同的信號(hào)。 TIM2時(shí)鐘設(shè)置為36MHz，預(yù)分頻設(shè)置為2，使用輸出比較-翻轉(zhuǎn)模式（Output Compare Toggle Mode）。 TIM2計(jì)數(shù)器時(shí)鐘可表達(dá)為：TIM2 counter clock = TIMxCLK / (Prescaler +1) = 12 MHz 設(shè)置TIM2_CCR1寄存器值為32768，則CC1更新頻率為TIM2計(jì)數(shù)器時(shí)鐘頻率除以CCR1寄存器值，為366.2 Hz。因此，TIM2通道1可產(chǎn)生一個(gè)頻率為183.1 Hz的周期信號(hào)。 同理，根據(jù)寄存器TIM2_CCR2 、TIM2_CCR3和 TIM2_CCR4的值，TIM2通道2可產(chǎn)生一個(gè)頻率為366.3 Hz的周期信號(hào)；TIM2通道3可產(chǎn)生一個(gè)頻率為732.4 Hz的周期信號(hào)；TIM2通道4可產(chǎn)生一個(gè)頻率為1464.8 Hz的周期信號(hào)。 可以通過(guò)示波器觀察各路輸出
上傳時(shí)間： 2014-01-22
上傳用戶：plsee
This course is about "distributed algorithms".Distributed algorithms include a wide range of parallel algorithms,which can be classified by a variety of attributes.
標(biāo)簽： algorithms Distributed distributed include
上傳時(shí)間： 2014-10-30
上傳用戶：baitouyu
編寫程序，登錄幼兒園200個(gè)小朋友的數(shù)據(jù)：姓名、性別、年齡、身高、體重、出生日期，分別按年齡排序后輸出。 要求： （1）登錄數(shù)據(jù)用函數(shù)input() （2）按身高排序用函數(shù)sort() （3）輸出排序結(jié)果用函數(shù)output()，輸出格式為： 幼兒園小朋友一覽（依身高排序） =================================================== 姓名 性別 年齡 身高 出生日期 …… … …… ……
上傳時(shí)間： 2013-12-30
上傳用戶：fhzm5658
輸入、輸出功能，檢驗(yàn)輸入的數(shù)是否為數(shù)字功能，ASCII碼與二進(jìn)制數(shù)的的相互轉(zhuǎn)化功能，兩數(shù)相乘功能，因此整個(gè)程序定義了兩個(gè)宏INPUT和MULTIPLE，宏INPUT實(shí)現(xiàn)了輸入、檢驗(yàn)和ASCII碼與二進(jìn)制的相互轉(zhuǎn)換功能，MULTIPLE實(shí)現(xiàn)了兩數(shù)相乘功能，實(shí)現(xiàn)輸出功能的是子程序OUTPUT，由于在輸入的過(guò)程中多次用到了回車換行，因此定義了一個(gè)回車換行子程序CRLF。
上傳時(shí)間： 2017-02-08
上傳用戶：Ants
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