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<pre id="kw4ss"></pre> // -*- Mode: Verilog -*- // Filename : wb_master.v // Description : Wishbone Master Behavorial // Author : Winefred Washington // Created On : 2002 12 24 // Last Modified By: . // Last Modified On: . // Update Count : 0 // Status : Unknown, Use with caution! // Description Specification // General Description: 8, 16, 32-bit WISHBONE Master // Supported cycles: MASTER, READ/WRITE // MASTER, BLOCK READ/WRITE // MASTER, RMW // Data port, size: 8, 16, 32-bit // Data port, granularity 8-bit // Data port, Max. operand size 32-bit // Data transfer ordering: little endian // Data transfer sequencing: undefined
標(biāo)簽： Description Behavorial wb_master Filename
上傳時間： 2014-07-11
上傳用戶：zhanditian
Multi-label classification 和weka集成
標(biāo)簽： classification Multi-label weka 集成
上傳時間： 2013-12-13
上傳用戶：bibirnovis
SPI Master Core Specification，This document provides specifications for the SPI (Serial Peripheral Interface) Master core
標(biāo)簽： Specification Master Core SPI
上傳時間： 2016-10-27
上傳用戶：lacsx
Multicast Algorithms for Multi-Channel Wireless Mesh Networks
標(biāo)簽： Multi-Channel Algorithms Multicast Wireless
上傳時間： 2014-01-12
上傳用戶：as275944189
profibus Master Slave PROGRAMS profibus Master Slave PROGRAMS
標(biāo)簽： profibus PROGRAMS Master Slave
上傳時間： 2016-11-05
上傳用戶：ywqaxiwang
RBFMIP is a package for training multi-instance RBF neural networks
標(biāo)簽： multi-instance networks training package
上傳時間： 2014-01-23
上傳用戶：refent
BPMLL is a package for training multi-label BP neural networks. The package includes the MATLAB code of the algorithm BP-MLL, which is designed to deal with multi-label learning. It is in particular useful when a real-world object is associated with multiple labels simultaneously
標(biāo)簽： package multi-label includes networks
上傳時間： 2013-12-05
上傳用戶：xsnjzljj
CCE is a multi-instance learning method solving multi-instance problems through adapting multi-instance representation to single-instance algorithms, which is quite different from existing multi-instance learning algorithms which attempt to adapt single-instance algorithms to multi-instance representation
標(biāo)簽： multi-instance multi-insta adapting learning
上傳時間： 2014-01-14
上傳用戶：manlian
This toolbox contains re-implementations of four different multi-instance learners, i.e. Diverse Density, Citation-kNN, Iterated-discrim APR, and EM-DD. Ensembles of these single multi-instance learners can be built with this toolbox
標(biāo)簽： i.e. re-implementations multi-instance different
上傳時間： 2013-12-19
上傳用戶：haohaoxuexi
MICROCHIP 實現(xiàn)I2C的 Master 端 (Firmware) 及 Slave 端 (Hardware) 相對應(yīng)的程式範(fàn)例
標(biāo)簽： MICROCHIP Firmware Hardware Master
上傳時間： 2014-01-08
上傳用戶：yimoney
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