2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP)最新文献_第6页

Edge-based motion and intensity prediction for video super-resolution 基于边缘的视频超分辨率运动和强度预测

2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP) Pub Date : 2014-12-01 DOI: 10.1109/GlobalSIP.2014.7032279

Jen-Wen Wang, C. Chiu

引用次数: 3

Cooperative capacity-achieving precoding design for multi-user VFDM transmission 多用户VFDM传输的协同容量实现预编码设计

2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP) Pub Date : 2014-12-01 DOI: 10.1109/GlobalSIP.2014.7032332

Rugui Yao, Yinsheng Liu, Lu Lu, Geoffrey Y. Li, A. Maaref

引用次数: 3

One-bit principal subspace estimation 位主子空间估计

2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP) Pub Date : 2014-12-01 DOI: 10.1109/GlobalSIP.2014.7032151

Yuejie Chi

引用次数: 2

Multi-policy posterior sampling for restless Markov bandits 不安马尔可夫强盗的多策略后验抽样

2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP) Pub Date : 2014-12-01 DOI: 10.1109/GlobalSIP.2014.7032327

Suleman Alnatheer, H. Man

引用次数: 1

Randomized Kaczmarz algorithms: Exact MSE analysis and optimal sampling probabilities 随机Kaczmarz算法:精确的MSE分析和最佳抽样概率

2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP) Pub Date : 2014-12-01 DOI: 10.1109/GlobalSIP.2014.7032145

Ameya Agaskar, C. Wang, Yue M. Lu

引用次数: 31

2D instantaneous frequency-based method for motion estimation using total variation 基于二维瞬时频率的全变分运动估计方法

2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP) Pub Date : 2014-12-01 DOI: 10.1109/GlobalSIP.2014.7032273

V. Murray, P. Rodríguez, M. Pattichis

引用次数: 2

Augmented speech production based on real-time statistical voice conversion 基于实时统计语音转换的增强语音生成

2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP) Pub Date : 2014-12-01 DOI: 10.1109/GlobalSIP.2014.7032186

T. Toda

{"title":"Augmented speech production based on real-time statistical voice conversion","authors":"T. Toda","doi":"10.1109/GlobalSIP.2014.7032186","DOIUrl":"https://doi.org/10.1109/GlobalSIP.2014.7032186","url":null,"abstract":"In human-to-human speech communication, various barriers are caused by some constraints, such as physical constraints causing vocal disorders and environmental constraints making it hard to produce intelligible speech. These barriers would be overcome if our speech production was augmented so that we could produce speech sounds as we want beyond these constraints. Voice conversion (VC) is a technique for modifying speech acoustics, converting non-/para-linguistic information to any form we want while preserving the linguistic content. One of the most popular approaches to VC is based on statistical processing, which is capable of extracting a complex conversion function in a data-driven manner. Although this technique was originally studied in the context of speaker conversion, which converts the voice of a certain speaker to sound like that of another specific speaker, it has great potential to achieve various applications beyond speaker conversion. This paper briefly reviews a trajectory-based conversion method that is capable of effectively reproducing natural speech parameter trajectories utterance by utterance and highlights several techniques that extend this trajectory-based conversion method to achieve real-time conversion processing. Finally this paper shows some examples of real-time VC applications to enhance human-to-human speech communication, such as speaking-aid, silent speech communication, and voice changer/vocal effector.","PeriodicalId":362306,"journal":{"name":"2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","volume":"125 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116370342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 18

Power-saving heterogeneous networks through optimal small-cell scheduling 基于最优小蜂窝调度的节能异构网络

2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP) Pub Date : 2014-12-01 DOI: 10.1109/GlobalSIP.2014.7032104

Shijie Cai, Lingjie Duan, Jing Wang, Rui Zhang

{"title":"Power-saving heterogeneous networks through optimal small-cell scheduling","authors":"Shijie Cai, Lingjie Duan, Jing Wang, Rui Zhang","doi":"10.1109/GlobalSIP.2014.7032104","DOIUrl":"https://doi.org/10.1109/GlobalSIP.2014.7032104","url":null,"abstract":"Traditional macro-cell networks are experiencing an explosion of data traffic, and small-cell can efficiently solve this problem by efficiently offloading the traffic from macro-cells. Given massive small-cells deployed in each over-crowed macro-cell, their aggregate power consumption (though low for an individual) can be larger than that of a macro-cell. To reduce the total power consumption of a whole heterogeneous network (HetNet) including macro-cells and small-cells, we dynamically schedule the operating modes of all small-cells (active or sleeping) in each macro-cell, while keeping the macro-cell active to avoid any service failure in coverage. When mobile users (MUs) are homogeneously distributed in a macro-cell according to a Poisson point process (PPP), we optimally propose small-cell location-based scheduling scheme to progressively decide the states of small-cells according to their distances to the corresponding macro-cell base station. Finally, we turn to a more general case where MUs are heterogeneously distributed in different small-cells. We first prove that the optimal scheduling problem is NP-hard and then propose a location-and-coverage-based scheduling algorithm which gives a suboptimal solution in polynomial-time. Simulation results show that the performance loss of our proposed algorithm is less than 1 percentage from the perspective of network power consumption.","PeriodicalId":362306,"journal":{"name":"2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125667534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

High-speed multi-block-row layered decoding for Quasi-cyclic LDPC codes 准循环LDPC码的高速多块行分层解码

2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP) Pub Date : 2014-12-01 DOI: 10.1109/GlobalSIP.2014.7032068

Xinmiao Zhang, Y. Tai

引用次数: 2

HEVC-based lossless compression of Whole Slide pathology images 基于hevc的全切片病理图像无损压缩

2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP) Pub Date : 2014-12-01 DOI: 10.1109/GlobalSIP.2014.7032126

Victor Sanchez, Francesc Aulí Llinàs, Joan Bartrina-Rapesta, J. Serra-Sagristà

引用次数: 18