International Conference on Digital Signal Processing proceedings : DSP. International Conference on Digital Signal Processing最新文献_第3页

Experimental research on Doppler spread of reverberation using PTFM signals PTFM信号混响多普勒扩频的实验研究

International Conference on Digital Signal Processing proceedings : DSP. International Conference on Digital Signal Processing Pub Date : 2016-01-01 DOI: 10.1109/ICDSP.2016.7868548

Xiao Tong Wang, R. Guo, Z. Cai

引用次数: 0

Study on attacking and defending techniques in IPv6 networks IPv6网络攻击与防御技术研究

International Conference on Digital Signal Processing proceedings : DSP. International Conference on Digital Signal Processing Pub Date : 2015-07-21 DOI: 10.1109/ICDSP.2015.7251328

Wu Liu, Ping Ren, Donghong Sun, Yawei Zhao, Ke Liu

引用次数: 2

Significant difference analysis of myocardial ischemia indicators based on synthesized algorithm 基于综合算法的心肌缺血指标显著性差异分析

International Conference on Digital Signal Processing proceedings : DSP. International Conference on Digital Signal Processing Pub Date : 2015-07-21 DOI: 10.1109/ICDSP.2015.7251843

Cong Wang, Xiaomei Wu

引用次数: 2

A new method of synthesizing chaotic music for tinnitus sound therapy 合成混沌音乐治疗耳鸣的新方法

International Conference on Digital Signal Processing proceedings : DSP. International Conference on Digital Signal Processing Pub Date : 2015-01-01 DOI: 10.1109/ICDSP.2015.7251875

Jiemei Chen, Peiyu He, Fan Pan

引用次数: 2

Decorrelating transforms for spectral vector quantization 光谱矢量量化的去相关变换

International Conference on Digital Signal Processing proceedings : DSP. International Conference on Digital Signal Processing Pub Date : 2013-07-01 DOI: 10.1109/ICDSP.2013.6622682

M. A. Ramírez

{"title":"Decorrelating transforms for spectral vector quantization","authors":"M. A. Ramírez","doi":"10.1109/ICDSP.2013.6622682","DOIUrl":"https://doi.org/10.1109/ICDSP.2013.6622682","url":null,"abstract":"Split vector quantization (SVQ) performs well and efficiently for line spectral frequency (LSF) quantization, but misses some component dependencies. Switched SVQ (SSVQ) can restore some advantage due to nonlinear dependencies through Gaussian Mixture Models (GMM). Remaining linear dependencies or correlations between vector components can be used to advantage by transform coding. The Karhunen-Loeve transform (KLT) is normally used but eigendecomposition and full transform matrices make it computationally complex. However, a family of transforms has been recently characterized by the capability of generalized triangular decomposition (GTD) of the source covariance matrix. The prediction-based lower triangular transform (PLT) is the least complex of such transforms and is a component in the implementation of all of them. This paper proposes a minimum noise structure for PLT SVQ. Coding results for 16-dimensional LSF vectors from wideband speech show that GMM PLT SSVQ can achieve transparent quantization down to 41 bit/frame with distortion performance close to GMM KLT SSVQ at about three-fourths as much operational complexity. Other members of the GTD family, such as the geometric mean decomposition (GMD) transform and the bidiagonal (BID) transform, fail to capitalize on their advantageous features due to the low bit rate per component in the range tested.","PeriodicalId":88900,"journal":{"name":"International Conference on Digital Signal Processing proceedings : DSP. International Conference on Digital Signal Processing","volume":"119 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2013-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84383712","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: 0

Adaptive radar detection and localization of a point-like target in homogeneous environment 均匀环境下点目标的自适应雷达探测与定位

International Conference on Digital Signal Processing proceedings : DSP. International Conference on Digital Signal Processing Pub Date : 2011-07-06 DOI: 10.1109/ICDSP.2011.6005009

D. Orlando, G. Ricci

引用次数: 0

ESTIMATION OF DIRECTIONAL BRAIN ANISOTROPY FROM EEG SIGNALS USING THE MELLIN TRANSFORM AND IMPLICATIONS FOR SOURCE LOCALIZATION. 利用mellin变换估计脑电信号的定向各向异性及其对脑电信号源定位的意义。

International Conference on Digital Signal Processing proceedings : DSP. International Conference on Digital Signal Processing Pub Date : 2011-07-06 DOI: 10.1109/ICDSP.2011.6004976

Catherine Stamoulis, Bernard S Chang

{"title":"ESTIMATION OF DIRECTIONAL BRAIN ANISOTROPY FROM EEG SIGNALS USING THE MELLIN TRANSFORM AND IMPLICATIONS FOR SOURCE LOCALIZATION.","authors":"Catherine Stamoulis, Bernard S Chang","doi":"10.1109/ICDSP.2011.6004976","DOIUrl":"https://doi.org/10.1109/ICDSP.2011.6004976","url":null,"abstract":"This paper presents a novel approach for the estimation of frequency-specific EEG scale modulations by the directional anisotropy of the brain, using the Mellin transform [1, 2, 3]. In the case of epileptic sources, the activity recorded by routine scalp EEG includes contributions not only from a seizure's primary propagation path but also from secondary paths and unrelated to the seizure activity. In addition, the anisotropy of the brain directionally modulates the seizure-related signal component. We estimated patient-specific direction-specific, frequency-locked scale shifts. During the ictal interval, these shifts occurred at frequencies ≥50 Hz. We further estimated the effect of scale modulations on time-delay estimation. Larger time-delays were estimated from EEGs that had been corrected by a scale factor prior to this estimation. Thus, corrections for non-linear scaling of EEGs may ultimately improve time-delay estimation for source localization, particularly in cases of seizures rapidly propagating to large areas of the brain.","PeriodicalId":88900,"journal":{"name":"International Conference on Digital Signal Processing proceedings : DSP. International Conference on Digital Signal Processing","volume":"2011 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2011-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/ICDSP.2011.6004976","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"30911480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Speech enhancement using speaker dependent codebooks 语音增强使用扬声器依赖码本

International Conference on Digital Signal Processing proceedings : DSP. International Conference on Digital Signal Processing Pub Date : 2011-01-01 DOI: 10.1109/ICDSP.2011.6004910

D. H. R. Naidu, G. V. P. Rao, Sriram Srinivasan

引用次数: 0

Estimation of Eeg Signal Dispersion During Seizure Propagation. 癫痫发作传播过程中脑电信号弥散的估计。

International Conference on Digital Signal Processing proceedings : DSP. International Conference on Digital Signal Processing Pub Date : 2009-09-18 DOI: 10.1109/ICDSP.2009.5201214

Catherine Stamoulis, Bernard S Chang, Joseph R Madsen

{"title":"Estimation of Eeg Signal Dispersion During Seizure Propagation.","authors":"Catherine Stamoulis, Bernard S Chang, Joseph R Madsen","doi":"10.1109/ICDSP.2009.5201214","DOIUrl":"https://doi.org/10.1109/ICDSP.2009.5201214","url":null,"abstract":"Localization of the seizure focus in the brain is a challenging problem in the field of epilepsy. The complexity of the seizure-related EEG waveform, its non-stationarity and degradation with distance due to the dispersive nature of the brain as a propagation medium, make localization difficult. Yet, precise estimation of the focus is critical, particularly when surgical resection is the only therapeutic option. The first step to solving this inverse problem is to estimate and account for frequency- or mode-specific signal dispersion, which is present in both scalp and intracranial EEG recordings during seizures. We estimated dispersion curves in both types of signals using a spatial correlation method and mode-based semblance analysis. We showed that, despite the assumption of spatial stationarity and a simplified array geometry, there is measurable inter-modal and intra-modal dispersion during seizures in both types of EEG recordings, affecting the estimated arrival times and consequently focus localization.","PeriodicalId":88900,"journal":{"name":"International Conference on Digital Signal Processing proceedings : DSP. International Conference on Digital Signal Processing","volume":"2009 ","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2009-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/ICDSP.2009.5201214","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"28958862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Force feature spaces for visualization and classification. 用于可视化和分类的强制特征空间。

International Conference on Digital Signal Processing proceedings : DSP. International Conference on Digital Signal Processing Pub Date : 2008-12-11 DOI: 10.1109/ICMLA.2008.46

Dragana Veljkovic, Kay A Robbins

引用次数: 3