VECTOR MICROSAR Technical References (AUTOSAR技术参考手册),包含BSW中各个功能模块的详细说明。
2020-01-03 11:17:34 96.3MB AUTOSA MICROS
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Vector Magic汉化破解版(位图转矢量图工具)下载 v1.15中文汉化版
2019-12-21 22:24:55 12.08MB Vector Magic 位图转矢量图
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《Sensorless Vector and Direct Torque Control》无速度控制的经典教材
2019-12-21 22:21:40 24.19MB Sensorless
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Vector公司的dbc文件格式说明文档,详细说明了dbc文件中各标识符的定义。
2019-12-21 22:17:39 158KB DBC Format Vector
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VECTOR产品手册
2019-12-21 22:15:47 2.11MB 恒润科技 Vetor 产品手册
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MSR Identity Toolbox: A Matlab Toolbox for Speaker Recognition Research Version 1.0 Seyed Omid Sadjadi, Malcolm Slaney, and Larry Heck Microsoft Research, Conversational Systems Research Center (CSRC) s.omid.sadjadi@gmail.com, {mslaney,larry.heck}@microsoft.com This report serves as a user manual for the tools available in the Microsoft Research (MSR) Identity Toolbox. This toolbox contains a collection of Matlab tools and routines that can be used for research and development in speaker recognition. It provides researchers with a test bed for developing new front-end and back-end techniques, allowing replicable evaluation of new advancements. It will also help newcomers in the field by lowering the “barrier to entry”, enabling them to quickly build baseline systems for their experiments. Although the focus of this toolbox is on speaker recognition, it can also be used for other speech related applications such as language, dialect and accent identification. In recent years, the design of robust and effective speaker recognition algorithms has attracted significant research effort from academic and commercial institutions. Speaker recognition has evolved substantially over the past 40 years; from discrete vector quantization (VQ) based systems to adapted Gaussian mixture model (GMM) solutions, and more recently to factor analysis based Eigenvoice (i-vector) frameworks. The Identity Toolbox provides tools that implement both the conventional GMM-UBM and state-of-the-art i-vector based speaker recognition strategies. A speaker recognition system includes two primary components: a front-end and a back-end. The front-end transforms acoustic waveforms into more compact and less redundant representations called acoustic features. Cepstral features are most often used for speaker recognition. It is practical to only retain the high signal-to-noise ratio (SNR) regions of the waveform, therefore there is also a need for a speech activity detector (SAD) in the fr
2019-12-21 22:11:04 2.32MB i-vactor
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此文档为PPT,内容是对于刷写工具vFlash的功能以及原理进行详细的介绍。
2019-12-21 22:09:43 1.54MB Vector vFlash 刷写工具
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此视频是恒润对于Vector CCP代码集成的介绍,适合对CCP代码集成初学者
2019-12-21 22:09:42 35.39MB CCP Vector 代码集成
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VECTOR的can标定协议代码.只需稍微修改即实现通过canape实现ccp相关命令功能.
2019-12-21 22:07:26 2.86MB CCP
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Vector官方帮助文档,配置使用手册。从新建DaVinci工程开始一步一步的讲解如何配置工程;如何编译生成C代码;如何导入CDD、DBC等文件。手册讲解细致,可以说是手把手教学了
2019-12-21 22:07:22 8.89MB AutoSAR Vector Davinci 配置手册
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