2016 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA)最新文献

{"title":"Asynchronous down-link cooperative communication scheme in Rayleigh fading wireless environment","authors":"Ahmed Desouky, A. El-Mahdy","doi":"10.1109/SPA.2016.7763602","DOIUrl":"https://doi.org/10.1109/SPA.2016.7763602","url":null,"abstract":"In this paper, a down-link cooperative communication scheme is proposed using full-rate Quasi-Orthogonal Space-time Block Codes (QOSTBC), employing asynchronous mobile Decode and Forward (DF) relays in a Rayleigh fading wireless environment. The channel used is a partially-coherent relay channel (PCRC), where the first hop is non-coherent and the second is coherent. Base station broadcasts using four transmitting antennas, towards all relay nodes in range over the first hop. Each intermediate relay uses Minimum Decoding Complexity (MDC) decoder achieving linear complexity. A relay selection technique is applied, electing the best performing intermediate nodes based on the channel response and path loss due to location relative to the destination node. A power allocation technique is adopted, which ranks based on the chosen relays performance. Relays transmit over four pre-defined time slots per frame. The destination node uses a Maximum-Likelihood (ML) decoder.","PeriodicalId":413894,"journal":{"name":"2016 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125334728","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}

{"title":"Smile veracity recognition using 3D texture features for image sequence processing","authors":"K. Nurzynska, B. Smolka","doi":"10.1109/SPA.2016.7763599","DOIUrl":"https://doi.org/10.1109/SPA.2016.7763599","url":null,"abstract":"Emotions are one of the most important cues of non-verbal communication, therefore are easily recognized by people. However, correct identification of intentions causes many problems, because telling apart the true emotion expression from the fake one is difficult. Therefore, there is a wide search nowadays for automatic techniques, which use computers to analyze behavior of people and learn the differences between spontaneous and posed emotional gestures. In this research we concentrate on the analysis of facial expressions in order to recognize between Duchenne (real) and fake smiles. Our approach treats the input movie as a dynamic texture and exploits LBP-TOP technique for its description. Additionally, the average facial image is removed from consideration as it is assumed, that only tiny changes differ the smile characters. The results obtained on UVA-NEMO dataset proved that it is possible to classify accurately between the spontaneous and posed smiles. Moreover, the influence of facial parts as well as changes due to a phase of smile are investigated.","PeriodicalId":413894,"journal":{"name":"2016 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA)","volume":"72 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122902291","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}

{"title":"DIAST variability illuminated thermal and visible ear images datasets","authors":"Syed Mohd Zahid Syed Zainal Ariffin, N. Jamil, P. Rahman","doi":"10.1109/SPA.2016.7763611","DOIUrl":"https://doi.org/10.1109/SPA.2016.7763611","url":null,"abstract":"As the research in ear biometrics grows, there is a need to have a publicly available ear images database for researchers to test and validate their methods. There are many available ear databases captured in visible light domain. However, images in those databases are mostly acquired in a controlled environment, not in naturally illuminated environments. Up to the point of writing, there is no thermalbased ear image dataset available for research usage. In this paper, we introduce our ear image datasets that were captured in both visible and thermal domain. We present the detailed process of image acquisition, post-processing, and preparation of the ear datasets. The ear dataset consists of 2,200 images captured from 55 subjects in five different illumination conditions, ranging from 2 lux to 10,700 lux, measured using lux meter.","PeriodicalId":413894,"journal":{"name":"2016 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA)","volume":"27 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114455056","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}

{"title":"High efficiency video coding","authors":"K. R. Rao","doi":"10.1109/SPA.2016.7763576","DOIUrl":"https://doi.org/10.1109/SPA.2016.7763576","url":null,"abstract":"In the family of video coding standards, HEVC has the promise and potential to replace/supplement all the existing standards (MPEG and H.26x series including H.264/AVC). While the complexity of the HEVC encoder is several times that of the H.264/AVC, the decoder complexity is within the range of the latter. Researchers are exploring about reducing the HEVC encoder complexity · Kim et al have shown that motion estimation (ME) occupies 77–81% of HEVC encoder implementation. Hence the focus has been in reducing the ME complexity. Several researchers have implemented performance comparison of HEVC with other standards such as H.264/AVC, MPEG-4 Part 2 visual, H.262/PEG-2 Video, H.263, and VP9 and also with image coding standards such as JPEG2000, JPEG-LS, and JPEG-XR. Several tests have shown that HEVC provides improved compression efficiency up to 50% bit rate reduction for the same subjective video quality compared to H.264/AVC. Besides addressing all current applications, HEVC is designed and developed to focus on two key issues: increased video resolution — up to 8k×4k — and increased use of parallel processing architecture. Brief description of the HEVC is provided. However for details and implementation, the reader is referred to the JCT-VC documents, overview papers, keynote speeches, tutorials, panel discussions, poster sessions, special issues, test models (TM/HM), web/ftp site, open source software, test sequences, anchor bit streams and the latest books on HEVC. Also researchers are exploring transcoding between HEVC and other standards such as MPEG-2 and H.264. Further extensions to HEVC are scalable video coding (SVC), 3D video/multiview video coding and range extensions which include screen content coding (SCC), bit depths larger than 10 bits and color sampling of 4:2:2 and 4:4:4. SCC in general refers to computer generated objects and screen shots from computer applications (both images and videos) and may require lossless coding. Some of these extensions have been finalized by the end of 2014 (time frame for SCC is late 2016). They also provide fertile ground for R & D. Iguchi et al have already developed a hardware encoder for super hi-vision (SHV) i.e., ultra HDTV at 7680×4320 pixel resolution. Also real-time hardware implementation of HEVC encoder for 1080p HD video has been done. NHK is planning SHV experimental broadcasting in 2016. A 249-Mpixel/s HEVC video decoder chip for 4k Ultra-HD applications has already been developed. Bross et al have shown that real time software decoding of 4K (3840×2160) video with HEVC is feasible on current desktop CPUs using four CPU cores. They also state that encoding 4K video in real time on the other hand is a challenge. Multimedia research group (MRC) predicts 2 billion HEVC based devices by end of 2016.","PeriodicalId":413894,"journal":{"name":"2016 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116676293","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}

{"title":"Selective interference alignment in 5G networks","authors":"Sarah Imam, A. El-Mahdy","doi":"10.1109/SPA.2016.7763603","DOIUrl":"https://doi.org/10.1109/SPA.2016.7763603","url":null,"abstract":"The evolving fifth generation (5G) cellular wireless networks provide higher data rates, enhanced end-user quality-of-experience (QoE), reduced end-to-end latency, and lower energy consumption. The 5G networks will consist of macrocells, femtocells and picocells with heterogeneous characteristics and capacities which will result in a multi-tier architecture. Hence, interference is one of the main problems in such systems and it will cause degradation in the system performance. Interference alignment techniques can be used to solve this problem. In this paper, a proposed cross-tier interference management algorithm for coexisting two-tier networks is introduced. First at each receiver, we calculate the sum of the square of the channel gains from each macro user to this receiver and the average of those sum values is taken as a threshold. Macro users whose sum values are greater than this threshold are selected and aligned at the femto receiver. This alignment is done by using precoders at the transmitters. In the proposed algorithm, the subspace in which the interference signals would be aligned is identified then a distributed algorithm is applied to identify the precoders needed at the selected interferers. Numerical results demonstrate the effectiveness of selective interference alignment for uplink interference management. The Cumulative Distribution Function (CDF) is used to measure the system performance.","PeriodicalId":413894,"journal":{"name":"2016 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128319679","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}

{"title":"Real-time advanced speech enhancement using low-power, fixed-point hardware","authors":"D. Bismor, Krzysztof Bartnicki","doi":"10.1109/SPA.2016.7763588","DOIUrl":"https://doi.org/10.1109/SPA.2016.7763588","url":null,"abstract":"This paper describes a project aiming at development of an embedded system speech enhancement solution. It was assumed that a low-cost, low-power, fixed-point processor will be used. It was also assumed that both the stationary and nonstationary noises should be removed. To meet the assumptions, the EZDSP5535 evaluation board, with the TMS320C5535 fixed-point digital signal processor, was selected as a hardware platform. Three speech enhancement algorithms were implemented: the FIR filtering, the adaptive line enhancement, and the spectral subtraction. The last algorithm, being a frequency-domain algorithm, utilizes the FFT co-processor available in the TMS320C5535 chip. All the algorithms can work simultaneously. Examples of good final performance are shown.","PeriodicalId":413894,"journal":{"name":"2016 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131841212","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}

{"title":"Rough set-based classification of EEG signals related to real and imagery motion","authors":"P. Szczuko","doi":"10.1109/SPA.2016.7763583","DOIUrl":"https://doi.org/10.1109/SPA.2016.7763583","url":null,"abstract":"A rough set-based approach to classification of EEG signals registered while subjects were performing real and imagery motions is presented in the paper. The appropriate subset of EEG channels is selected, the recordings are segmented, and features are extracted, based on time-frequency decomposition of the signal. Rough set classifier is trained in several scenarios, comparing accuracy of classification for real and imagery motion. Results are commented and further research is proposed.","PeriodicalId":413894,"journal":{"name":"2016 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132867874","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}

{"title":"Computational models for predicting sound quality","authors":"B. Moore","doi":"10.1109/SPA.2016.7763577","DOIUrl":"https://doi.org/10.1109/SPA.2016.7763577","url":null,"abstract":"The quality of an audio device, such as a microphone, amplifier, or headphone, depends on how accurately the device transmits the properties of the sound source to the ear(s) of the listener. Two types of “distortion” can occur in this transmission: (1) “Linear” distortion, which may be described as a deviation of the frequency response from the “target” response; (2) Nonlinear distortion, which is characterised by frequency components in the output of the device that were not present in the input. These two forms of distortion have different perceptual effects. Their effects on sound quality can be predicted using a model of auditory processing with the following stages: (1) A filter to take into account the transmission of sound from the device to the ear of the listener; (2) A filter to simulate the effects of transmission through the middle ear; (3) An array of bandpass filters to simulate the auditory filters that exist in the cochlea of the inner ear. For predicting the perceptual effects of linear distortion, a model operating in the frequency domain can be used. For predicting the perceptual effects of nonlinear distortion, a model operating in the time domain is required, since the detailed waveforms at the outputs of the auditory filters need to be considered. The models described have been shown to give accurate predictions for a wide range of “artificial” and “real” linear and nonlinear distortions.","PeriodicalId":413894,"journal":{"name":"2016 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133772672","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}

{"title":"Multithreaded Java approach to speaker recognition","authors":"Radoslaw Weychan, T. Marciniak, A. Dabrowski","doi":"10.1109/SPA.2016.7763630","DOIUrl":"https://doi.org/10.1109/SPA.2016.7763630","url":null,"abstract":"In this paper an analysis of multithread approach to speaker recognition is presented. Two cases have been investigated — the use of multithreading first, to reduce the total time of training and testing (when processing the speaker database) and second, to reduce the time of a single speaker recognition (e.g. in voice-based access systems). We have investigated the processing time in function of a number of threads in order to find the optimal number for 8-core CPU. The obtained results show that the computation time can be reduced even over 5 times for this kind of processor. The prepared implementation is available on Github source code repository.","PeriodicalId":413894,"journal":{"name":"2016 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114306364","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}

{"title":"Performance analysis of proportionate-type LMS algorithms","authors":"Vinay Chakravarthi Gogineni, Subrahmanyam Mula, R. Das, M. Chakraborty","doi":"10.1109/SPA.2016.7763608","DOIUrl":"https://doi.org/10.1109/SPA.2016.7763608","url":null,"abstract":"For real-time sparse systems identification applications, Proportionate-type Least Mean Square (Pt-LMS) algorithms are often preferred to their normalized counterparts (Pt-NLMS) due to lower computational complexity of the former algorithms. In this paper, we present the convergence analysis of Pt-LMS algorithms. Without any assumptions on input, both first and second order convergence analysis are carried out and new convergence bounds are obtained. In particular, it establishes the universality of the steady-state mean square deviation. Detailed simulation results are presented to validate the analytical results.","PeriodicalId":413894,"journal":{"name":"2016 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114576034","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}