Pub Date : 2014-12-01DOI: 10.1109/GlobalSIP.2014.7032229
Pengfei Liu, Xiaohan Wang, Yuantao Gu
Graph signal coarsening is a kind of dimensionality reduction in irregular domain. Given a graph signal, it aims to simultaneously obtain a coarser version of the graph and a coarsened signal on the new graph. In this work, we explore the design space for the graph signal coarsening problem and show that solutions can be split into four categories. We propose an effective method that uses a successive approach and spectral-domain-based signal coarsening for solving the problem, which is the first that falls into one of the four categories. Experiments are conducted to show the effectiveness of the proposed method.
{"title":"Graph signal coarsening: Dimensionality reduction in irregular domain","authors":"Pengfei Liu, Xiaohan Wang, Yuantao Gu","doi":"10.1109/GlobalSIP.2014.7032229","DOIUrl":"https://doi.org/10.1109/GlobalSIP.2014.7032229","url":null,"abstract":"Graph signal coarsening is a kind of dimensionality reduction in irregular domain. Given a graph signal, it aims to simultaneously obtain a coarser version of the graph and a coarsened signal on the new graph. In this work, we explore the design space for the graph signal coarsening problem and show that solutions can be split into four categories. We propose an effective method that uses a successive approach and spectral-domain-based signal coarsening for solving the problem, which is the first that falls into one of the four categories. Experiments are conducted to show the effectiveness of the proposed method.","PeriodicalId":362306,"journal":{"name":"2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","volume":"123 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":"129003374","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 : 2014-12-01DOI: 10.1109/GlobalSIP.2014.7032282
Hsin-Che Liu, H. Hang
In the virtual-view 3D video coding system, both the RGB image data and the depth maps are compressed and translated to the receivers. After compression, the depth maps are distorted and may cause visible artifacts on the synthesized video. We study the visual effect of compressed depth maps on the synthesized video and develop a quality assessment model that predicts the subjective quality. We use HEVC Test Model (HTM) to compress the depth maps. The distorted depth value may lead to ghost artifacts around object edges and unnatural object motion on the synthesized video. In our proposed quality assessment (QA) model, we use SSIM to compute the basic score of stereo image pair; we extract the edge, motion, and depth features of stereo pairs and combine them to form a local weight to increase the sensitivity of the noticeable regions. We use the binocular perception model to calculate the score of stereo pairs. We conduct our own subjective tests. The results of our experiments show that our model has a better match to the subjective scores when it is compared with the other existing metrics.
{"title":"Quality assessment of synthesized 3D video with distorted depth map","authors":"Hsin-Che Liu, H. Hang","doi":"10.1109/GlobalSIP.2014.7032282","DOIUrl":"https://doi.org/10.1109/GlobalSIP.2014.7032282","url":null,"abstract":"In the virtual-view 3D video coding system, both the RGB image data and the depth maps are compressed and translated to the receivers. After compression, the depth maps are distorted and may cause visible artifacts on the synthesized video. We study the visual effect of compressed depth maps on the synthesized video and develop a quality assessment model that predicts the subjective quality. We use HEVC Test Model (HTM) to compress the depth maps. The distorted depth value may lead to ghost artifacts around object edges and unnatural object motion on the synthesized video. In our proposed quality assessment (QA) model, we use SSIM to compute the basic score of stereo image pair; we extract the edge, motion, and depth features of stereo pairs and combine them to form a local weight to increase the sensitivity of the noticeable regions. We use the binocular perception model to calculate the score of stereo pairs. We conduct our own subjective tests. The results of our experiments show that our model has a better match to the subjective scores when it is compared with the other existing metrics.","PeriodicalId":362306,"journal":{"name":"2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","volume":"95 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":"129282313","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 : 2014-12-01DOI: 10.1109/GlobalSIP.2014.7032166
Sung-Hsien Hsieh, Chun-Shien Lu, S. Pei
The existing dictionary learning methods mostly focus on ID signals, leading to the disadvantage of incurring overload of memory and computation if the size of training samples is large enough. Recently, 2D dictionary learning paradigm has been validated to save massive memory usage, especially for large-scale problems. To address this issue, we propose novel 2D dictionary learning algorithms based on tensors in this paper. Our learning problem is efficiently solved by CANDECOMP/PARAFAC (CP) decomposition. In addition, our algorithms guarantee sparsity constraint, which makes that sparse representation of the learned dictionary is equivalent to the ground truth. Experimental results confirm the effectness of our methods.
{"title":"2D sparse dictionary learning via tensor decomposition","authors":"Sung-Hsien Hsieh, Chun-Shien Lu, S. Pei","doi":"10.1109/GlobalSIP.2014.7032166","DOIUrl":"https://doi.org/10.1109/GlobalSIP.2014.7032166","url":null,"abstract":"The existing dictionary learning methods mostly focus on ID signals, leading to the disadvantage of incurring overload of memory and computation if the size of training samples is large enough. Recently, 2D dictionary learning paradigm has been validated to save massive memory usage, especially for large-scale problems. To address this issue, we propose novel 2D dictionary learning algorithms based on tensors in this paper. Our learning problem is efficiently solved by CANDECOMP/PARAFAC (CP) decomposition. In addition, our algorithms guarantee sparsity constraint, which makes that sparse representation of the learned dictionary is equivalent to the ground truth. Experimental results confirm the effectness of our methods.","PeriodicalId":362306,"journal":{"name":"2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","volume":"5 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":"115811551","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 : 2014-12-01DOI: 10.1109/GlobalSIP.2014.7032138
Hongbiao Gao, M. Asghari, B. Jalali
We introduce a method for arbitrary waveform generation employing time bandwidth product expansion. It is based on the newly introduced mathematical function, Anamorphic Stretch Transform for engineering the time bandwidth of signals. We show that using warped dispersive Fourier transform with a specific frequency to time mapping profile, one can boost the time-bandwidth product of waveform generators above the fundamental limit set by spectral encoding. This report is the first application of anamorphic stretch transform for waveform generation.
{"title":"Time-bandwidth engineering for arbitrary waveform generation","authors":"Hongbiao Gao, M. Asghari, B. Jalali","doi":"10.1109/GlobalSIP.2014.7032138","DOIUrl":"https://doi.org/10.1109/GlobalSIP.2014.7032138","url":null,"abstract":"We introduce a method for arbitrary waveform generation employing time bandwidth product expansion. It is based on the newly introduced mathematical function, Anamorphic Stretch Transform for engineering the time bandwidth of signals. We show that using warped dispersive Fourier transform with a specific frequency to time mapping profile, one can boost the time-bandwidth product of waveform generators above the fundamental limit set by spectral encoding. This report is the first application of anamorphic stretch transform for waveform generation.","PeriodicalId":362306,"journal":{"name":"2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","volume":"9 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":"115860849","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 : 2014-12-01DOI: 10.1109/GlobalSIP.2014.7032237
E. Shahrivar, S. Sundaram
We introduce a two-player network formation game based on the classical Colonel Blotto game. We consider a scenario where there is a common set of nodes and each player in the game designs a network layer by purchasing a set of edges between these nodes. We assume that players have a limited budget with which to bid on each edge and the utility of a given set of edges to a player is a function of the resulting network layer. We characterize the ranges of player budgets for which the game admits pure Nash equilibria for utility functions that depend on the component sizes and diameter of the formed networks.
{"title":"Multi-layer network formation via a Colonel Blotto game","authors":"E. Shahrivar, S. Sundaram","doi":"10.1109/GlobalSIP.2014.7032237","DOIUrl":"https://doi.org/10.1109/GlobalSIP.2014.7032237","url":null,"abstract":"We introduce a two-player network formation game based on the classical Colonel Blotto game. We consider a scenario where there is a common set of nodes and each player in the game designs a network layer by purchasing a set of edges between these nodes. We assume that players have a limited budget with which to bid on each edge and the utility of a given set of edges to a player is a function of the resulting network layer. We characterize the ranges of player budgets for which the game admits pure Nash equilibria for utility functions that depend on the component sizes and diameter of the formed networks.","PeriodicalId":362306,"journal":{"name":"2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","volume":"15 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":"116005610","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 : 2014-12-01DOI: 10.1109/GlobalSIP.2014.7032195
Zhilin Chen, Chenyang Yang
This paper deals with the pilot contamination problem for massive MIMO systems. Considering the sparse nature of channel impulse response inherent in wideband systems, the paths of channels of the desired and interference users hardly arrive at the same time, which allows most paths of desired channel to be distinguishable from the paths of interference channels in time-domain. Based on this observation, we first estimate the power delay profile (PDP) of the desired channel with the contaminated channel estimate, from which we acquire the delay of each path of the desired channel. By extracting the corresponding channel components from the contaminated channel estimate, a clean channel estimate can be obtained. To reduce the impact of pilot contamination on the estimated PDP, we propose a pilot assignment method among adjacent cells to randomize the interference over successive uplink frames. Simulation results demonstrate substantial sum rate gain of the proposed approach over existing methods.
{"title":"Pilot decontamination in massive MIMO systems: Exploiting channel sparsity with pilot assignment","authors":"Zhilin Chen, Chenyang Yang","doi":"10.1109/GlobalSIP.2014.7032195","DOIUrl":"https://doi.org/10.1109/GlobalSIP.2014.7032195","url":null,"abstract":"This paper deals with the pilot contamination problem for massive MIMO systems. Considering the sparse nature of channel impulse response inherent in wideband systems, the paths of channels of the desired and interference users hardly arrive at the same time, which allows most paths of desired channel to be distinguishable from the paths of interference channels in time-domain. Based on this observation, we first estimate the power delay profile (PDP) of the desired channel with the contaminated channel estimate, from which we acquire the delay of each path of the desired channel. By extracting the corresponding channel components from the contaminated channel estimate, a clean channel estimate can be obtained. To reduce the impact of pilot contamination on the estimated PDP, we propose a pilot assignment method among adjacent cells to randomize the interference over successive uplink frames. Simulation results demonstrate substantial sum rate gain of the proposed approach over existing methods.","PeriodicalId":362306,"journal":{"name":"2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","volume":"18 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":"125419258","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 : 2014-12-01DOI: 10.1109/GlobalSIP.2014.7032094
M. O. Sayin, N. D. Vanli, Tolga Goze, S. Kozat
We study diffusion based channel estimation in distributed architectures suitable for various communication applications such as cognitive radios. Although the demand for distributed processing is steadily growing, these architectures require a substantial amount of communication among their nodes (or processing elements) causing significant energy consumption and increase in carbon footprint. Due to growing awareness of telecommunication industry's impact on the environment, the need to mitigate this problem is indisputable. To this end, we introduce algorithms significantly reducing the communication load between distributed nodes, which is the main cause in energy consumption, while providing outstanding performance. In this framework, after each node produces its local estimate of the communication channel, a single bit or a couple of bits of information is generated using certain random projections. This newly generated data is diffused and then used in neighboring nodes to recover the original full information, i.e., the channel estimate of the desired communication channel. We provide the complete state-space description of these algorithms and demonstrate the substantial gains through our experiments.
{"title":"Communication efficient channel estimation over distributed networks","authors":"M. O. Sayin, N. D. Vanli, Tolga Goze, S. Kozat","doi":"10.1109/GlobalSIP.2014.7032094","DOIUrl":"https://doi.org/10.1109/GlobalSIP.2014.7032094","url":null,"abstract":"We study diffusion based channel estimation in distributed architectures suitable for various communication applications such as cognitive radios. Although the demand for distributed processing is steadily growing, these architectures require a substantial amount of communication among their nodes (or processing elements) causing significant energy consumption and increase in carbon footprint. Due to growing awareness of telecommunication industry's impact on the environment, the need to mitigate this problem is indisputable. To this end, we introduce algorithms significantly reducing the communication load between distributed nodes, which is the main cause in energy consumption, while providing outstanding performance. In this framework, after each node produces its local estimate of the communication channel, a single bit or a couple of bits of information is generated using certain random projections. This newly generated data is diffused and then used in neighboring nodes to recover the original full information, i.e., the channel estimate of the desired communication channel. We provide the complete state-space description of these algorithms and demonstrate the substantial gains through our experiments.","PeriodicalId":362306,"journal":{"name":"2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","volume":"341 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":"125771479","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 : 2014-12-01DOI: 10.1109/GlobalSIP.2014.7032119
Lei Xu, Chunxiao Jiang, Yan Chen, Yong Ren, K. Liu
Collaborative filtering (CF) is widely used in recommendation systems. A user can get good recommendations only when both the user himself/herself and other users actively participate, i.e. providing sufficient rating data. However, due to the rating cost, rational users tend to provide as few ratings as possible. Therefore, there exists a trade-off between the rating cost and recommendation quality. In this paper, we model the interactions among users as a game in satisfaction form and study the corresponding equilibrium, namely satisfaction equilibrium (SE). Considering that accumulated rating data are used for recommendation, we design a behavior rule which allows users to achieve a SE via iteratively rating items. Experimental results based on real data demonstrate that, if all users have moderate expectations for recommendation quality and satisfied users are willing to provide more ratings, then all users can get satisfying recommendations without providing too many ratings. The SE analysis of the proposed game in this paper is helpful for designing mechanisms to encourage user participation.
{"title":"User participation game in collaborative filtering","authors":"Lei Xu, Chunxiao Jiang, Yan Chen, Yong Ren, K. Liu","doi":"10.1109/GlobalSIP.2014.7032119","DOIUrl":"https://doi.org/10.1109/GlobalSIP.2014.7032119","url":null,"abstract":"Collaborative filtering (CF) is widely used in recommendation systems. A user can get good recommendations only when both the user himself/herself and other users actively participate, i.e. providing sufficient rating data. However, due to the rating cost, rational users tend to provide as few ratings as possible. Therefore, there exists a trade-off between the rating cost and recommendation quality. In this paper, we model the interactions among users as a game in satisfaction form and study the corresponding equilibrium, namely satisfaction equilibrium (SE). Considering that accumulated rating data are used for recommendation, we design a behavior rule which allows users to achieve a SE via iteratively rating items. Experimental results based on real data demonstrate that, if all users have moderate expectations for recommendation quality and satisfied users are willing to provide more ratings, then all users can get satisfying recommendations without providing too many ratings. The SE analysis of the proposed game in this paper is helpful for designing mechanisms to encourage user participation.","PeriodicalId":362306,"journal":{"name":"2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","volume":"14 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":"126022686","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 : 2014-12-01DOI: 10.1109/GlobalSIP.2014.7032362
Xiangfang Li, Sunday Ogedengbe, Lijun Qian, E. Dougherty
The complexity of biological signaling networks, especially the uncertainties associated with the model parameters, present challenges for understanding the behavior of such networks and hence hamper the translation of the modeling study into drug development process. Sensitivity analysis can help to determine which parameters are the "key drivers" of the model's output. How to tailor the sensitivity study under drug perturbation based on the knowledge of available existing or potential drugs are considered in this paper. The goal is to evaluate the drug effect on the signaling pathway modeled by kinetic rate changes. Through an example simulation study of the response of NF-κB pathway to two drugs, it is observed that new or modified sensitivity analysis methods may be necessary for the purpose of drug effect study. In addition, the new method may also help us determine whether combination therapy can yield significant synergism when compared to their individual drug effect.
{"title":"Sensitivity analysis for drug effect study: An NF-κB pathway example","authors":"Xiangfang Li, Sunday Ogedengbe, Lijun Qian, E. Dougherty","doi":"10.1109/GlobalSIP.2014.7032362","DOIUrl":"https://doi.org/10.1109/GlobalSIP.2014.7032362","url":null,"abstract":"The complexity of biological signaling networks, especially the uncertainties associated with the model parameters, present challenges for understanding the behavior of such networks and hence hamper the translation of the modeling study into drug development process. Sensitivity analysis can help to determine which parameters are the \"key drivers\" of the model's output. How to tailor the sensitivity study under drug perturbation based on the knowledge of available existing or potential drugs are considered in this paper. The goal is to evaluate the drug effect on the signaling pathway modeled by kinetic rate changes. Through an example simulation study of the response of NF-κB pathway to two drugs, it is observed that new or modified sensitivity analysis methods may be necessary for the purpose of drug effect study. In addition, the new method may also help us determine whether combination therapy can yield significant synergism when compared to their individual drug effect.","PeriodicalId":362306,"journal":{"name":"2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","volume":"77 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":"126712912","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}
The minimum variance distortionless response (MV-DR) beamformer is very sensitive to the steering vector mismatch. Such mismatch can lead to serious degradation of the beamforming performance especially at high signal-to-noise ratio (SNR). In this paper, a new robust beamformer based on the DOA matrix is proposed to solve the steering vector mismatch. Through the left eigendecomposition of the DOA matrix, a subspace which is orthogonal to the interference subspace can be obtained and is further used to construct the beamforming weight vector. Simulation results show the effectiveness of our proposed method.
{"title":"DOA matrix based robust beamforming in the presence of steering vector mismatch","authors":"Wei Guo, Pengcheng Mu, Jiancun Fan, Huiming Wang, Qinye Yin","doi":"10.1109/GlobalSIP.2014.7032289","DOIUrl":"https://doi.org/10.1109/GlobalSIP.2014.7032289","url":null,"abstract":"The minimum variance distortionless response (MV-DR) beamformer is very sensitive to the steering vector mismatch. Such mismatch can lead to serious degradation of the beamforming performance especially at high signal-to-noise ratio (SNR). In this paper, a new robust beamformer based on the DOA matrix is proposed to solve the steering vector mismatch. Through the left eigendecomposition of the DOA matrix, a subspace which is orthogonal to the interference subspace can be obtained and is further used to construct the beamforming weight vector. Simulation results show the effectiveness of our proposed method.","PeriodicalId":362306,"journal":{"name":"2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","volume":"7 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":"127126760","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}
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