Design and VLSI implementation of a digital audio-specific DSP core for MP3_AAC
標簽： implementation audio-specific digital Design
上傳時間： 2016-10-21
上傳用戶：ljmwh2000
Multi-label classification 和weka集成
標簽： classification Multi-label weka 集成
上傳時間： 2013-12-13
上傳用戶：bibirnovis
With the advent of multimedia, digital signal processing (DSP) of sound has emerged from the shadow of bandwidth-limited speech processing. Today, the main appli- cations of audio DSP are high quality audio coding and the digital generation and manipulation of music signals. They share common research topics including percep- tual measurement techniques and analysis/synthesis methods. Smaller but nonetheless very important topics are hearing aids using signal processing technology and hardware architectures for digital signal processing of audio. In all these areas the last decade has seen a significant amount of application oriented research.
標簽： multimedia processing the digital
上傳時間： 2014-01-23
上傳用戶：xwd2010
It is about digital image processingand photomechanical printing2
標簽： photomechanical processingand printing2 digital
上傳時間： 2016-10-26
上傳用戶：l254587896
Discription: This multi-master driver provides the software interface to the I2C Bus hardware of the M3062x series of MitsubishiMCU.
標簽： multi-master Discription interface the
上傳時間： 2016-10-28
上傳用戶：ljt101007
Multicast Algorithms for Multi-Channel Wireless Mesh Networks
標簽： Multi-Channel Algorithms Multicast Wireless
上傳時間： 2014-01-12
上傳用戶：as275944189
RBFMIP is a package for training multi-instance RBF neural networks
標簽： 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
標簽： i.e. re-implementations multi-instance different
上傳時間： 2013-12-19
上傳用戶：haohaoxuexi
