Pub Date : 2008-12-08DOI: 10.1109/ICOSP.2008.4697536
Ke Xiong, Z. Qiu, Hong-ke Zhang
Quality of Service (QoS) parameter aggregation is essential to Inter-domain QoS routing. It is the goal that how to aggregate Intra-domain QoS state with less data and less information losses. This Paper proposed a geometry-based approach to represent the QoS state information of delay and bandwidth for a subnetwork. We use regular polyline to approximate the service support area and just six tuples are needed to represent the aggregated information in our scheme. Both of the processes of aggregation and restore are introduced. Simulations and comparisons show that our scheme has the lower aggregation error ratio than existing approaches.
QoS (Quality of Service)参数聚合是域间QoS路由的关键。如何以更少的数据和更少的信息丢失来聚合域内QoS状态是目标。提出了一种基于几何的表示子网时延和带宽的QoS状态信息的方法。我们使用常规折线来近似服务支持区域，并且只需要六个元组来表示我们方案中的聚合信息。介绍了聚合和还原的过程。仿真和比较表明，该方案具有较低的聚合误差率。
{"title":"QoS state information aggregation for Inter-domain routing","authors":"Ke Xiong, Z. Qiu, Hong-ke Zhang","doi":"10.1109/ICOSP.2008.4697536","DOIUrl":"https://doi.org/10.1109/ICOSP.2008.4697536","url":null,"abstract":"Quality of Service (QoS) parameter aggregation is essential to Inter-domain QoS routing. It is the goal that how to aggregate Intra-domain QoS state with less data and less information losses. This Paper proposed a geometry-based approach to represent the QoS state information of delay and bandwidth for a subnetwork. We use regular polyline to approximate the service support area and just six tuples are needed to represent the aggregated information in our scheme. Both of the processes of aggregation and restore are introduced. Simulations and comparisons show that our scheme has the lower aggregation error ratio than existing approaches.","PeriodicalId":445699,"journal":{"name":"2008 9th International Conference on Signal Processing","volume":"66 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131693608","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}
Pub Date : 2008-12-08DOI: 10.1109/ICOSP.2008.4697705
M. Kayvanrad
A practical method of reconstruction of signals from a small number of random observations is put forward. The method takes advantage of the sparsity of the signal in wavelet domain to reconstruct it in an iterative manner. The proposed method is shown to be quite successful in reconstruction of 1D as well as 2D signals from a few numbers of randomly acquired samples. It also proves to be robust to observation noise.
{"title":"Reconstruction from random measurements","authors":"M. Kayvanrad","doi":"10.1109/ICOSP.2008.4697705","DOIUrl":"https://doi.org/10.1109/ICOSP.2008.4697705","url":null,"abstract":"A practical method of reconstruction of signals from a small number of random observations is put forward. The method takes advantage of the sparsity of the signal in wavelet domain to reconstruct it in an iterative manner. The proposed method is shown to be quite successful in reconstruction of 1D as well as 2D signals from a few numbers of randomly acquired samples. It also proves to be robust to observation noise.","PeriodicalId":445699,"journal":{"name":"2008 9th International Conference on Signal Processing","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131795928","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}
Pub Date : 2008-12-08DOI: 10.1109/ICOSP.2008.4697506
Hua Zhong, Linhua Zheng, Guoping Jin
Decision feedback equalization (DFE) has been widely used to compensate ISI for filter multitone (FMT) systems. However, DFE is limited especially when the nonlinear distortion becomes severe. In this paper, a novel equalizer structure based on FLANN is proposed for FMT system to eliminate the nonlinear distortion caused by the communication channel. The proposed equalizer structure is shown to outperform DFE especially when nonlinear distortion occurs. It can therefore be considered as a better alternative for FMT equalization.
{"title":"Nonlinear channel equalization for filtered multi-tone modulation system using functional link artificial neural networks","authors":"Hua Zhong, Linhua Zheng, Guoping Jin","doi":"10.1109/ICOSP.2008.4697506","DOIUrl":"https://doi.org/10.1109/ICOSP.2008.4697506","url":null,"abstract":"Decision feedback equalization (DFE) has been widely used to compensate ISI for filter multitone (FMT) systems. However, DFE is limited especially when the nonlinear distortion becomes severe. In this paper, a novel equalizer structure based on FLANN is proposed for FMT system to eliminate the nonlinear distortion caused by the communication channel. The proposed equalizer structure is shown to outperform DFE especially when nonlinear distortion occurs. It can therefore be considered as a better alternative for FMT equalization.","PeriodicalId":445699,"journal":{"name":"2008 9th International Conference on Signal Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130776627","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}
Pub Date : 2008-12-08DOI: 10.1109/ICOSP.2008.4697057
S. Kumar Sahoo, M. Kumar Singh, Srikrishna
This paper presents a novel architecture for a high speed finite impulse response (FIR) filter. The design of proposed filter is based on a computation sharing multiplier algorithm with reduced addition implementation. The proposed filter is very efficient, as it gives a significant improvement in speed with a reduction in size of adder circuits. The performance of the proposed filter is compared with implementation based on carry save multiplier in 0.13 mum technology. The proposed filter improves speed by approximately 50% with respect to FIR filter implementations based on carry-save multiplier.
{"title":"High speed FIR Filter design based on sharing multiplication using dual channel adder and compressor","authors":"S. Kumar Sahoo, M. Kumar Singh, Srikrishna","doi":"10.1109/ICOSP.2008.4697057","DOIUrl":"https://doi.org/10.1109/ICOSP.2008.4697057","url":null,"abstract":"This paper presents a novel architecture for a high speed finite impulse response (FIR) filter. The design of proposed filter is based on a computation sharing multiplier algorithm with reduced addition implementation. The proposed filter is very efficient, as it gives a significant improvement in speed with a reduction in size of adder circuits. The performance of the proposed filter is compared with implementation based on carry save multiplier in 0.13 mum technology. The proposed filter improves speed by approximately 50% with respect to FIR filter implementations based on carry-save multiplier.","PeriodicalId":445699,"journal":{"name":"2008 9th International Conference on Signal Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130808663","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}
Pub Date : 2008-12-08DOI: 10.1109/ICOSP.2008.4697285
Quan Liu, Yong Su
A multiple blind watermarking scheme is proposed in this paper, which bases on RGB color image decomposition and embeds watermarks in the spatial domain and wavelet domain of gray images decomposed. This method increases the quantity of watermarks embedded, and does not require the original image or original watermarks when extracting watermarks. With the knowledge of cryptography and scrambling transform and chaos theory applied in the paper, the anti-attack capability of watermarks is improved. The extracting process relies entirely on keys. So the security is enhanced. Experimental results demonstrate that this method has better robustness to the shear attack, salt and pepper noise when embedding watermark in the spatial domain and has better robustness to the white Gaussian noise, JPEG compression, and other attacks when embedding watermark in the wavelet domain.
{"title":"A multiple blind watermark algorithm based on spatial and wavelet domain","authors":"Quan Liu, Yong Su","doi":"10.1109/ICOSP.2008.4697285","DOIUrl":"https://doi.org/10.1109/ICOSP.2008.4697285","url":null,"abstract":"A multiple blind watermarking scheme is proposed in this paper, which bases on RGB color image decomposition and embeds watermarks in the spatial domain and wavelet domain of gray images decomposed. This method increases the quantity of watermarks embedded, and does not require the original image or original watermarks when extracting watermarks. With the knowledge of cryptography and scrambling transform and chaos theory applied in the paper, the anti-attack capability of watermarks is improved. The extracting process relies entirely on keys. So the security is enhanced. Experimental results demonstrate that this method has better robustness to the shear attack, salt and pepper noise when embedding watermark in the spatial domain and has better robustness to the white Gaussian noise, JPEG compression, and other attacks when embedding watermark in the wavelet domain.","PeriodicalId":445699,"journal":{"name":"2008 9th International Conference on Signal Processing","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130994535","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}
Pub Date : 2008-12-08DOI: 10.1109/ICOSP.2008.4697558
Jiwen Lu, Yongwei Zhao, Yanxue Xue, Junlin Hu
This paper proposes an efficient palmprint recognition method using locality preserving projections (LPP) and extreme learning machine (ELM) neural network. Firstly, two-dimensional discrete wavelet transformation (DWT) is applied in the region of interest (ROI) of each palmprint image and then principal component analysis (PCA) and LPP are used for dimensionality reduction. Finally, we construct a single-hidden layer forward network (SLFN) to construct one extreme learning machine (ELM) to quickly classify the palmprint images. Experiments on the PolyU palmprint database demonstrate the effectiveness of the proposed method.
{"title":"Palmprint recognition via Locality Preserving Projections and extreme learning machine neural network","authors":"Jiwen Lu, Yongwei Zhao, Yanxue Xue, Junlin Hu","doi":"10.1109/ICOSP.2008.4697558","DOIUrl":"https://doi.org/10.1109/ICOSP.2008.4697558","url":null,"abstract":"This paper proposes an efficient palmprint recognition method using locality preserving projections (LPP) and extreme learning machine (ELM) neural network. Firstly, two-dimensional discrete wavelet transformation (DWT) is applied in the region of interest (ROI) of each palmprint image and then principal component analysis (PCA) and LPP are used for dimensionality reduction. Finally, we construct a single-hidden layer forward network (SLFN) to construct one extreme learning machine (ELM) to quickly classify the palmprint images. Experiments on the PolyU palmprint database demonstrate the effectiveness of the proposed method.","PeriodicalId":445699,"journal":{"name":"2008 9th International Conference on Signal Processing","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132837171","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}
Pub Date : 2008-12-08DOI: 10.1109/ICOSP.2008.4697190
Xia Zou, Xiongwei Zhang
An efficient multi-mode predictive multistage matrix quantization is proposed for very low bit rate quantization of line spectral frequencies (LSF) in LPC based speech coder. One novel aspect of the proposed technique is the mode based predictor and quantizer. Another novel aspect is the optimization of the predictive coefficients considering the mode transition between successive superframes and the connection between predictor and quantizer. Experimental results show that the proposed method yields higher quality LSF quantizer at very low bit rate than those designed with several recently proposed methods.
{"title":"Efficient coding of LSF parameters using multi-mode predictive multistage matrix quantization","authors":"Xia Zou, Xiongwei Zhang","doi":"10.1109/ICOSP.2008.4697190","DOIUrl":"https://doi.org/10.1109/ICOSP.2008.4697190","url":null,"abstract":"An efficient multi-mode predictive multistage matrix quantization is proposed for very low bit rate quantization of line spectral frequencies (LSF) in LPC based speech coder. One novel aspect of the proposed technique is the mode based predictor and quantizer. Another novel aspect is the optimization of the predictive coefficients considering the mode transition between successive superframes and the connection between predictor and quantizer. Experimental results show that the proposed method yields higher quality LSF quantizer at very low bit rate than those designed with several recently proposed methods.","PeriodicalId":445699,"journal":{"name":"2008 9th International Conference on Signal Processing","volume":"149 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133515334","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}
Pub Date : 2008-12-08DOI: 10.1109/ICOSP.2008.4697444
H. Men, Yujie Wu, Yanchun Gao, Xiaoying Li, Shanrang Yang
Support vector machine (SVM) is applied for classification in this paper. The SVM operates on the principle of structure risk minimization; hence better generalization ability is guaranteed. This paper discussed the basic principle of the SVM at first, and then we chose SVM classifier with polynomial kernel and the Gaussian radial basis function kernel (RBFSVM) to recognize the cancer samples (benign and malignant). Selecting some value for parameters to know different performance each parameter produces to outputs. The simulations of the recognizing of two class samples have been presented and discussed. Results show the RBF SVM can classify complicated patterns and achieve higher recognition rate. SVM overcomes disadvantages of the artificial neural networks. The results indicate that the SVM classifier exhibits good generalization performance and the recognition rate above 93.33% for the testing samples. This means the support vector machines are effective for classification.
{"title":"Application of support vector machine to pattern classification","authors":"H. Men, Yujie Wu, Yanchun Gao, Xiaoying Li, Shanrang Yang","doi":"10.1109/ICOSP.2008.4697444","DOIUrl":"https://doi.org/10.1109/ICOSP.2008.4697444","url":null,"abstract":"Support vector machine (SVM) is applied for classification in this paper. The SVM operates on the principle of structure risk minimization; hence better generalization ability is guaranteed. This paper discussed the basic principle of the SVM at first, and then we chose SVM classifier with polynomial kernel and the Gaussian radial basis function kernel (RBFSVM) to recognize the cancer samples (benign and malignant). Selecting some value for parameters to know different performance each parameter produces to outputs. The simulations of the recognizing of two class samples have been presented and discussed. Results show the RBF SVM can classify complicated patterns and achieve higher recognition rate. SVM overcomes disadvantages of the artificial neural networks. The results indicate that the SVM classifier exhibits good generalization performance and the recognition rate above 93.33% for the testing samples. This means the support vector machines are effective for classification.","PeriodicalId":445699,"journal":{"name":"2008 9th International Conference on Signal Processing","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133276677","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}
Pub Date : 2008-12-08DOI: 10.1109/ICOSP.2008.4697058
D. Farrokhi, R. Togneri, A. Zaknich
A post processing technique is proposed to enhance speech in a single channel system. A new noise estimation algorithm is proposed in conjunction with the Controlled Forward March Averaging (CFMA) technique to enhance speech in a single channel non-stationary noisy system. We introduce a 9-Dimensional Noise Estimation (NDNE) algorithm to the Single Channel Speech Estimation (SCSE) system, that updates the estimated noise in 9 frequency sub-bands, by averaging the noisy speech power spectrum using a time and frequency dependent smoothing factor. A signal presence probability factor is calculated by computing the ratio of the noisy speech power spectrum to its local minimum, which is computed by averaging past values of the noisy speech power spectra with a look-ahead factor. The NDNE uses a non-linear thresholding map as oppose to the conventional linear thresholding. This new algorithm produced an average 7% improvement in 0 and -2.5 dB global SNR in speech corrupted with modified Babble noise. Subjective tests confirmed these results.
{"title":"Single channel speech enhancement using a 9 Dimensional Noise Estimation algorithm and Controlled Forward March Averaging","authors":"D. Farrokhi, R. Togneri, A. Zaknich","doi":"10.1109/ICOSP.2008.4697058","DOIUrl":"https://doi.org/10.1109/ICOSP.2008.4697058","url":null,"abstract":"A post processing technique is proposed to enhance speech in a single channel system. A new noise estimation algorithm is proposed in conjunction with the Controlled Forward March Averaging (CFMA) technique to enhance speech in a single channel non-stationary noisy system. We introduce a 9-Dimensional Noise Estimation (NDNE) algorithm to the Single Channel Speech Estimation (SCSE) system, that updates the estimated noise in 9 frequency sub-bands, by averaging the noisy speech power spectrum using a time and frequency dependent smoothing factor. A signal presence probability factor is calculated by computing the ratio of the noisy speech power spectrum to its local minimum, which is computed by averaging past values of the noisy speech power spectra with a look-ahead factor. The NDNE uses a non-linear thresholding map as oppose to the conventional linear thresholding. This new algorithm produced an average 7% improvement in 0 and -2.5 dB global SNR in speech corrupted with modified Babble noise. Subjective tests confirmed these results.","PeriodicalId":445699,"journal":{"name":"2008 9th International Conference on Signal Processing","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133348800","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}
Pub Date : 2008-12-08DOI: 10.1109/ICOSP.2008.4697110
A. Montazeri, J. Poshtan
This study presents design and robust stability analysis of a novel version of RLS-type adaptive IIR filter in the modified filtered-x structure. The derivation of the algorithm is by transforming the original ANVC problem to an output-error identification problem without assuming that the slow adaptation condition holds. By considering fast adaptation of the filter weights and also the assumption that nonparametric uncertainty exists in the estimation of the secondary path, the stability of the proposed algorithm is analyzed using Lyapunov theory. In fact by introducing a time-varying scalar parameter in the adaptation, a sufficient condition based on the value of this parameter and the size of the uncertainty is derived.
{"title":"Design and analysis of an RLS-type modified filtered-x algorithm for adaptive IIR filters","authors":"A. Montazeri, J. Poshtan","doi":"10.1109/ICOSP.2008.4697110","DOIUrl":"https://doi.org/10.1109/ICOSP.2008.4697110","url":null,"abstract":"This study presents design and robust stability analysis of a novel version of RLS-type adaptive IIR filter in the modified filtered-x structure. The derivation of the algorithm is by transforming the original ANVC problem to an output-error identification problem without assuming that the slow adaptation condition holds. By considering fast adaptation of the filter weights and also the assumption that nonparametric uncertainty exists in the estimation of the secondary path, the stability of the proposed algorithm is analyzed using Lyapunov theory. In fact by introducing a time-varying scalar parameter in the adaptation, a sufficient condition based on the value of this parameter and the size of the uncertainty is derived.","PeriodicalId":445699,"journal":{"name":"2008 9th International Conference on Signal Processing","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133220257","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：