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Description: This example shows how to configure the Crossbar.-This example shows how to configure the Cro ssbar.
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Size: 1127 |
Author: hsy |
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Description: basic_hook_cr0,一个hook cro寄存器源代码，有很重要的参考价值-basic_hook_cr0, a hook tis Register source code, a very important reference value
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Size: 3084 |
Author: freducn2002 |
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Description: 交叉编译环境 交叉编译环境 交叉编译环境 -cross-compiler environment cro ss-compiler environment cro ss-compiler environment cro ss-compiler environment cro ss-compiler environment cro ss-compiler environment cross-compiler environment
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Size: 5738 |
Author: hepeixin |
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Description: This example shows how to configure the Crossbar.-This example shows how to configure the Cro ssbar.
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Size: 1024 |
Author: hsy |
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Description: basic_hook_cr0,一个hook cro寄存器源代码，有很重要的参考价值-basic_hook_cr0, a hook tis Register source code, a very important reference value
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Size: 3072 |
Author: freducn2002 |
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Description: 交叉编译环境 交叉编译环境 交叉编译环境 -cross-compiler environment cro ss-compiler environment cro ss-compiler environment cro ss-compiler environment cro ss-compiler environment cro ss-compiler environment cross-compiler environment
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Size: 5120 |
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Description: 用CROUT分解法求解三对角方程.对于对角占优的三对角方程可以求出数值稳定解.-Decomposition method used CROUT tridiagonal equations. For the diagonally dominant tridiagonal numerical stability equation solution can be obtained.
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Size: 212992 |
Author: 张鹏飞 |
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Description: 过零峰值幅度(ZCPA：Zero-cro ingwithPeakAmplitude)特征的语音识别系统，它是基于人耳的听觉模型建立起来的，这是ZCPA的源程序。-Zero-crossing peak amplitudes (ZCPA: Zero-cro ingwithPeakAmplitude) features voice recognition system, which is based on the model of the human ear
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Size: 617472 |
Author: 马致远 |
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Description: 已经保存了训练好的网络权值，所以第一次使用识别程序时，可以直接运行Release目录下的可执行文件，然后对图片目录中的测试图片进行读入、识别。当然也可以自行用训练样本训练网络，不过要注意训练样本的选择，否则可能识别率很低。训练样本选择的原则是，尽可能的有代表性，在训练时间不至于太长的情况下训练样本数目尽量多。
-Training has been well preserved network weights, so first use of identification procedures, you can directly run the Release directory of the executable file, and then on the picture of the test directory to read into the picture, identification. Of course, we can use training samples to train the network, but attention should be paid to the training sample selection, or may be very low recognition rate. Training sample selection principle is that there is as much as possible representative, at training time not too long a number of cases as many as possible training samples.
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Size: 1089536 |
Author: 高照明 |
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Description: 描述跨时钟域分析,分析和解决异步时钟同步设计问题.-Description of cross-clock domain analysis, analyze and solve design problems in asynchronous clock synchronization.
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Size: 478208 |
Author: 张然峰 |
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Description: 一款最新的国际象棋程序，作者Don Cro-A new chess program by Don Cross
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Size: 429056 |
Author: klack |
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Description: Genetic algorithms programs, uses different algorithms, such as the simple cro-Genetic algorithms programs, uses different algorithms, such as the simple cross
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Size: 15360 |
Author: perla |
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Description: decisor using energy and zero cro-decisor using energy and zero cross
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Size: 1024 |
Author: robertotelco |
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Description: ı t is about mı cro proccessor and ı t s aplication
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Size: 358400 |
Author: murat |
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Description: atmega32 cro rca display source code
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Size: 7168 |
Author: vignesh |
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Description: general Cathode ray oscilloscope introduction.
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Size: 280576 |
Author: shivaji |
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Description: CRO is new series of distributed DAQ card manufactured by ni company.
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Size: 1317888 |
Author: chenshuxue |
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Description: 嵌入维数自适应最小二乘支持向量机
状态时间序列预测方法
Condition Time Series Prediction Using Least Squares Support Vector Machine
with Adaptive Embedding Dimension
针对航空发动机状态时间序列预测中嵌入维数难于有效选取的问题, 提出一种基于嵌入维数自适应
最小二乘支持向量机( L SSVM ) 的预测方法。该方法将嵌入维数作为影响状态时间序列预测精度的重要参
数, 以交叉验证误差为评价准则, 利用粒子群优化( P SO ) 进化搜索LSSV M 预测模型的最优超参数与嵌入维
数, 同时通过矩阵变换原理提高交叉验证过程的计算效率, 并最终建立优化后的L SSVM 预测模型。航空发
动机排气温度( EGT ) 预测实例表明, 该方法可自适应选取适用于状态时间序列预测的最优嵌入维数且预测
精度高, 适用于航空发动机状态时间序列预测。- T o deal wit h the difficulty of selecting an appro pr iate embedding dimension for aeroeng ine co ndition
time series predictio n, a metho d based o n least squar es suppo rt vecto r machine ( L SSVM ) with ada ptive em
bedding dimension is pro po sed. I n the method, the embedding dimensio n is identified as a parameter that af
fects the accuracy o f the aer oengine condition time series predictio n par ticle sw arm o ptimizat ion ( P SO) is ap
plied to optimize the hyperpar ameter s and embedding dimension of the L SSV M pr edict ion model cro ssv alida
tion is applied to evaluate the perfo rmance o f the L SSVM predictio n mo del and matr ix tr ansfo rm is applied to
the L SSVM pr ediction model tr aining to accelerate the crossvalidation evaluation pro cess. Ex periments on an
aeroengine ex haust g as t emperatur e ( EGT ) predictio n demonst rates that the metho d is hig hly effective in em
bedding dimension selection. In compar ison w ith co nv
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Description: Chemical Reaction Optimization （CRO）是一种新兴的智能算法，PaperArtificial Chemical Reaction Optimization Algorithm for global optimization详细介绍了该算法，CRO为其Java代码，供新学者参考
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Size: 20480 |
Author: fqx |
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