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其他  This approach addresses two difficulties simultaneously: 1) the range limitation of mobile robot se

This approach addresses two difficulties simultaneously: 1) the range limitation of mobile robot sensors and 2) the difficulty of detecting buildings in monocular aerial images. With the suggested method building outlines can be detected faster than the mobile robot can explore the area by itself, g ...

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文章/文档  in this document, i make a compartion between two algorithms, computational cost, algorithm analysis

in this document, i make a compartion between two algorithms, computational cost, algorithm analysis, on c. excuse my english

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医药行业  临床医药试验：Gehan s Two Stage Design

临床医药试验：Gehan s Two Stage Design

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医药行业  临床医药试验:Simon s Two stage Design

临床医药试验:Simon s Two stage Design

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汇编语言  * * * * * * * Two wire/I2C Bus READ/WRITE Sample Routines of Microchip s 2

*** *** *** *** *** *** ***** ** Two wire/I2C Bus READ/WRITE Sample Routines of Microchip s ** 24Cxx / 85Cxx serial CMOS EEPROM interfacing to a ** PIC16C54 8-bit CMOS single chip microcomputer ** Revsied Version 2.0 (4/2/92). ** ** Part use = PIC16C54-XT/JW ** Note: 1) All timings are base ...

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数值算法/人工智能  Muscl Euler Two dimensions

Muscl Euler Two dimensions

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系统设计方案  measure through the cross-entropy of test data. In addition, we introduce two novel smoothing tech

measure through the cross-entropy of test data. In addition, we introduce two novel smoothing techniques, one a variation of Jelinek-Mercer smoothing and one a very simple linear interpolation technique, both of which outperform existing methods.

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人工智能/神经网络  ％ Train a two layer neural network with the Levenberg-Marquardt ％ method. ％％ If desired, it is p

％ 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, ％ ...

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matlab例程  Train a two layer neural network with a recursive prediction error ％ algorithm ("recursive Gauss-Ne

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 , w ...

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加密解密  This work briefly explains common cryptosystems and details two most popular private-key ciphers: DE

This work briefly explains common cryptosystems and details two most popular private-key ciphers: DES ,which is probably the most widely used, and AES, which is intended to replace DES.

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