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Titlebook: Communication and Networking; International Confer Tai-hoon Kim,Thanos Vasilakos,Dominik ?l?zak Conference proceedings 2010 Springer Berlin

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樓主: Adentitious
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發(fā)表于 2025-3-23 11:50:47 | 只看該作者
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Decision-Making Model Based on Capability Factors for Embedded Systems,prescribe best choice for evaluation of embedded systems (ES) is presented. The techniques utilize a combination of subjective and qualitative assumptions and mathematical modelling techniques. The digital cell phone as a sample of ES is analyzed as case study to show the application of the proposed
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發(fā)表于 2025-3-24 00:23:05 | 只看該作者
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發(fā)表于 2025-3-24 13:35:20 | 只看該作者
Complexity Reduction of WSOLA-Based Time-Scale Modification Using Signal Period Estimation,(TSM) algorithm using signal period estimation. In the proposed method, a signal period is estimated from the normalized cross-correlation. An optimal shift, a maximally similar point, of WSOLA for the current frame can be estimated from the estimated period obtained from the previous frame. Then, w
18#
發(fā)表于 2025-3-24 14:57:50 | 只看該作者
A Real-Time Audio Upmixing Method from Stereo to 7.1-Channel Audio,ixing method employs an adaptive panning and a decorrelation technique for making more channels and reproducing natural reverberant surround sounds, respectively. The performance of the proposed upmixing method is evaluated using a MUSHRA test and compared with those of conventional upmixing methods
19#
發(fā)表于 2025-3-24 22:36:26 | 只看該作者
Statistical Model-Based Voice Activity Detection Using Spatial Cues and Log Energy for Dual-Channelucted by spatial cues and log energy. In particular, spatial cues are composed of the interaural time differences and interaural level differences of dual-channel speech signals, and the statistical models for speech presence and absence are based on a Gaussian kernel density. In order to evaluate t
20#
發(fā)表于 2025-3-25 00:53:27 | 只看該作者
A Local Graph Clustering Algorithm for Discovering Subgoals in Reinforcement Learning,to cluster the agent state space. Subgoals discovered by the algorithm are then used to generate skills. Experimental results show that the proposed subgoal discovery algorithm has a dramatic effect on the learning performance.
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