Pub Date : 2016-12-01DOI: 10.1109/ISSPIT.2016.7886020
Takahiro Kitazawa, K. Ohuchi
Orthogonal Frequency Division Multiplexing (OFDM) signals suffer from high PAPR (Peak to Average Power Ratio). Cyclic shifted sequences (CSS) was proposed as a solution to high PAPR. CSS reduces PAPR stochastically by giving some independent cyclic shifts to the time-domain signals of clusters. In CSS, however, we must transmit side information (SI) regarding the cyclic shift. Although a blind method to estimate SI at the receiver was also proposed, its computational complexity increases as not only the number of subcarriers but also the degree of multi-level modulation increases. In the present paper, to conquer this drawback, we consider decreasing the number of subcarriers used for estimating SI. This paper shows that we achieve almost the same bit error rate as the conventional scheme with half the number of subcarriers under a certain condition. We also study the relationship between the number of subcarriers per cluster and estimation accuracy.
{"title":"On blind estimation with reduced complexity in CSS-OFDM systems","authors":"Takahiro Kitazawa, K. Ohuchi","doi":"10.1109/ISSPIT.2016.7886020","DOIUrl":"https://doi.org/10.1109/ISSPIT.2016.7886020","url":null,"abstract":"Orthogonal Frequency Division Multiplexing (OFDM) signals suffer from high PAPR (Peak to Average Power Ratio). Cyclic shifted sequences (CSS) was proposed as a solution to high PAPR. CSS reduces PAPR stochastically by giving some independent cyclic shifts to the time-domain signals of clusters. In CSS, however, we must transmit side information (SI) regarding the cyclic shift. Although a blind method to estimate SI at the receiver was also proposed, its computational complexity increases as not only the number of subcarriers but also the degree of multi-level modulation increases. In the present paper, to conquer this drawback, we consider decreasing the number of subcarriers used for estimating SI. This paper shows that we achieve almost the same bit error rate as the conventional scheme with half the number of subcarriers under a certain condition. We also study the relationship between the number of subcarriers per cluster and estimation accuracy.","PeriodicalId":371691,"journal":{"name":"2016 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127688702","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 : 2016-12-01DOI: 10.1109/ISSPIT.2016.7886016
F. Jin, F. Sattar
Automatic respiratory sound (RS) analysis provides a possible solution for the minimization of inherent subjectivity caused by auscultation via stethoscope, and it allows a reproducible quantification of RS. As one of the crucial initial steps, reliable unsupervised respiratory phase detection plays an important role in automatic RS analysis. In this paper, a novel unsupervised phase detection scheme is proposed using improved triplet markov chain (TMC) based statistical technique. The problems of the commonly used unsupervised respiratory phase detection techniques and their improvement with the proposed discriminative features are explored. The feasibility and limitations of this advanced statistical approach for respiratory phase detection are also addressed.
{"title":"Unsupervised phase detection for respiratory sounds using improved scale-space features","authors":"F. Jin, F. Sattar","doi":"10.1109/ISSPIT.2016.7886016","DOIUrl":"https://doi.org/10.1109/ISSPIT.2016.7886016","url":null,"abstract":"Automatic respiratory sound (RS) analysis provides a possible solution for the minimization of inherent subjectivity caused by auscultation via stethoscope, and it allows a reproducible quantification of RS. As one of the crucial initial steps, reliable unsupervised respiratory phase detection plays an important role in automatic RS analysis. In this paper, a novel unsupervised phase detection scheme is proposed using improved triplet markov chain (TMC) based statistical technique. The problems of the commonly used unsupervised respiratory phase detection techniques and their improvement with the proposed discriminative features are explored. The feasibility and limitations of this advanced statistical approach for respiratory phase detection are also addressed.","PeriodicalId":371691,"journal":{"name":"2016 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126931837","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 : 2016-12-01DOI: 10.1109/ISSPIT.2016.7886015
Christos Photiou, Evgenia Bousi, C. Pitris, I. Zouvani
Dispersion, resulting from wavelength-dependent index of refraction variations, could be used to detect changes associated with cancer for early and accurate diagnosis. Different techniques for estimating the dispersion from Optical Coherence Tomography (OCT) images were investigated to evaluate their accuracy and applicability to samples such as muscle and adipose tissue. The dispersion was estimated from (i) the point spread function (PSF) degradation, (ii) the shift (walk-off) between images taken at different center wavelengths and (iii) the second derivative of the spectral phase. A novel technique, which uses a Wiener-type deconvolution algorithm to calculate the PSF degradation from the image speckle and is, therefore, applicable in vivo and in situ is also presented. This method was applied to a set of normal and cancer gastrointestinal OCT images resulting in 93% sensitivity and 73% specificity. The success of these preliminary results indicates the potential of using dispersion measurements for disease diagnosis.
{"title":"Extracting dispersion information from Optical Coherence Tomography images","authors":"Christos Photiou, Evgenia Bousi, C. Pitris, I. Zouvani","doi":"10.1109/ISSPIT.2016.7886015","DOIUrl":"https://doi.org/10.1109/ISSPIT.2016.7886015","url":null,"abstract":"Dispersion, resulting from wavelength-dependent index of refraction variations, could be used to detect changes associated with cancer for early and accurate diagnosis. Different techniques for estimating the dispersion from Optical Coherence Tomography (OCT) images were investigated to evaluate their accuracy and applicability to samples such as muscle and adipose tissue. The dispersion was estimated from (i) the point spread function (PSF) degradation, (ii) the shift (walk-off) between images taken at different center wavelengths and (iii) the second derivative of the spectral phase. A novel technique, which uses a Wiener-type deconvolution algorithm to calculate the PSF degradation from the image speckle and is, therefore, applicable in vivo and in situ is also presented. This method was applied to a set of normal and cancer gastrointestinal OCT images resulting in 93% sensitivity and 73% specificity. The success of these preliminary results indicates the potential of using dispersion measurements for disease diagnosis.","PeriodicalId":371691,"journal":{"name":"2016 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114266527","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 : 2016-12-01DOI: 10.1109/ISSPIT.2016.7886044
F. Cholewa, M. Wielage, P. Pirsch, H. Blume
This paper introduces a new FPGA architecture optimized for Frequency Modulated Continuous Wave (FMCW) Synthetic Aperture Radar (SAR). The architecture implements a Global-Backprojection-Algorithm (GBP) which has been modified to be independent of platform velocity (start-stop-approximation). The design supports parallelism of dedicated GBP processing modules in order to provide high performance. Compared to a MATLAB implementation on a single core Intel i5 at 3.2 GHz the dedicated implementation on a ML605 board provides a minimum speed-up factor of 94. The entire FPGA system was tested with real-life SAR data.
{"title":"An FPGA architecture for velocity independent backprojection in FMCW-based SAR systems","authors":"F. Cholewa, M. Wielage, P. Pirsch, H. Blume","doi":"10.1109/ISSPIT.2016.7886044","DOIUrl":"https://doi.org/10.1109/ISSPIT.2016.7886044","url":null,"abstract":"This paper introduces a new FPGA architecture optimized for Frequency Modulated Continuous Wave (FMCW) Synthetic Aperture Radar (SAR). The architecture implements a Global-Backprojection-Algorithm (GBP) which has been modified to be independent of platform velocity (start-stop-approximation). The design supports parallelism of dedicated GBP processing modules in order to provide high performance. Compared to a MATLAB implementation on a single core Intel i5 at 3.2 GHz the dedicated implementation on a ML605 board provides a minimum speed-up factor of 94. The entire FPGA system was tested with real-life SAR data.","PeriodicalId":371691,"journal":{"name":"2016 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)","volume":"34 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132794778","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 : 2016-12-01DOI: 10.1109/ISSPIT.2016.7886059
S. Dimitriadis, P. Simos, N. Laskaris, S. Fotopoulos, J. Fletcher, D. Linden, A. Papanicolaou
Magnetoencephalography (MEG) is a brain imaging method affording real-time temporal, and adequate spatial resolution to reveal aberrant neurophysiological function associated with dyslexia. In this study we analyzed sensor-level resting-state neuromagnetic recordings from 25 reading-disabled children and 27 non-impaired readers under the notion of symbolic dynamics and complexity analysis. We compared two techniques for estimating the complexity of MEG time-series in each of 8 frequency bands based on symbolic dynamics: (a) Lempel-Ziv complexity (LZC) entailing binarization of each MEG time series using the mean amplitude as a threshold, and (b) An approach based on the neural-gas algorithm (NG) which has been used by our group in the context of various symbolization schemes. The NG approach transforms each MEG time series to more than two symbols by learning the reconstructed manifold of each time series with a small error. Using this algorithm we computed a complexity index (CI) based on the distribution of words up to a predetermined length. The relative performance of the two complexity indexes was assessed using a classification procedure based on k-NN and Support Vector Machines. Results revealed the capacity of CI to discriminate impaired from non-impaired readers with 80% accuracy. Corresponding performance of LZC values did not exceed 55%. These findings indicate that symbolization of MEG recordings with an appropriate neuroinformatic approach, such as the proposed CI metric, may be of value in understanding the neural dynamics of dyslexia.
{"title":"Classifying children with reading difficulties from non-impaired readers via symbolic dynamics and complexity analysis of MEG resting-state data","authors":"S. Dimitriadis, P. Simos, N. Laskaris, S. Fotopoulos, J. Fletcher, D. Linden, A. Papanicolaou","doi":"10.1109/ISSPIT.2016.7886059","DOIUrl":"https://doi.org/10.1109/ISSPIT.2016.7886059","url":null,"abstract":"Magnetoencephalography (MEG) is a brain imaging method affording real-time temporal, and adequate spatial resolution to reveal aberrant neurophysiological function associated with dyslexia. In this study we analyzed sensor-level resting-state neuromagnetic recordings from 25 reading-disabled children and 27 non-impaired readers under the notion of symbolic dynamics and complexity analysis. We compared two techniques for estimating the complexity of MEG time-series in each of 8 frequency bands based on symbolic dynamics: (a) Lempel-Ziv complexity (LZC) entailing binarization of each MEG time series using the mean amplitude as a threshold, and (b) An approach based on the neural-gas algorithm (NG) which has been used by our group in the context of various symbolization schemes. The NG approach transforms each MEG time series to more than two symbols by learning the reconstructed manifold of each time series with a small error. Using this algorithm we computed a complexity index (CI) based on the distribution of words up to a predetermined length. The relative performance of the two complexity indexes was assessed using a classification procedure based on k-NN and Support Vector Machines. Results revealed the capacity of CI to discriminate impaired from non-impaired readers with 80% accuracy. Corresponding performance of LZC values did not exceed 55%. These findings indicate that symbolization of MEG recordings with an appropriate neuroinformatic approach, such as the proposed CI metric, may be of value in understanding the neural dynamics of dyslexia.","PeriodicalId":371691,"journal":{"name":"2016 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133221787","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 : 2016-12-01DOI: 10.1109/ISSPIT.2016.7886053
Yusuke Kameda, Hiroyuki Kishi, Tomokazu Ishikawa, I. Matsuda, S. Itoh
We propose an efficient motion compensation method based on a temporally extrapolated frame by using a pel-wise motion (optical flow) estimation. In traditional motion compensation methods, motion vectors are generally detected on a block-by-block basis and sent to the decoder as side information. However, such block-wise motions are not always suitable for motions such as local scaling, rotation, and deformation. On the other hand, pel-wise motion can be estimated on both the side of the encoder and decoder from two successive frames that were previously encoded without side information. The use of pel-wise motion enables the extrapolated frame to be generated under the assumption of linear uniform motions within a short time period. This frame is an approximation of the frame to be encoded. The proposed bi-prediction method uses the extrapolated frame as one of the reference frames. The experimental results indicate that the prediction performance of the proposed method is higher than that of the traditional method.
{"title":"Multi-frame motion compensation using extrapolated frame by optical flow for lossless Video Coding","authors":"Yusuke Kameda, Hiroyuki Kishi, Tomokazu Ishikawa, I. Matsuda, S. Itoh","doi":"10.1109/ISSPIT.2016.7886053","DOIUrl":"https://doi.org/10.1109/ISSPIT.2016.7886053","url":null,"abstract":"We propose an efficient motion compensation method based on a temporally extrapolated frame by using a pel-wise motion (optical flow) estimation. In traditional motion compensation methods, motion vectors are generally detected on a block-by-block basis and sent to the decoder as side information. However, such block-wise motions are not always suitable for motions such as local scaling, rotation, and deformation. On the other hand, pel-wise motion can be estimated on both the side of the encoder and decoder from two successive frames that were previously encoded without side information. The use of pel-wise motion enables the extrapolated frame to be generated under the assumption of linear uniform motions within a short time period. This frame is an approximation of the frame to be encoded. The proposed bi-prediction method uses the extrapolated frame as one of the reference frames. The experimental results indicate that the prediction performance of the proposed method is higher than that of the traditional method.","PeriodicalId":371691,"journal":{"name":"2016 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134435437","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 : 2016-12-01DOI: 10.1109/ISSPIT.2016.7886026
K. Guo, Bangning Zhang, Yu-zhen Huang, D. Guo
In this paper, we analyze the secure performance of satellite communication networks in Shadowed Rician Channel. It is very important to analyze the secure performance of the satellite-terrestrial networks. In this paper, both the Alice, Bob and Eve are equipped with single antenna respectively. Specifically, the exact closed-form expressions for the probability of non-zero secrecy capacity, the secrecy outage probability and the average secrecy capacity are derived, which provide fast means to evaluate the system performance. In addition, the channel we assume is shadowed Rician (SR) channel, which is close to the reality. Finally, simulation results are provided to verify the correctness of the analytical results.
{"title":"Secure performance analysis of satellite communication networks in Shadowed Rician Channel","authors":"K. Guo, Bangning Zhang, Yu-zhen Huang, D. Guo","doi":"10.1109/ISSPIT.2016.7886026","DOIUrl":"https://doi.org/10.1109/ISSPIT.2016.7886026","url":null,"abstract":"In this paper, we analyze the secure performance of satellite communication networks in Shadowed Rician Channel. It is very important to analyze the secure performance of the satellite-terrestrial networks. In this paper, both the Alice, Bob and Eve are equipped with single antenna respectively. Specifically, the exact closed-form expressions for the probability of non-zero secrecy capacity, the secrecy outage probability and the average secrecy capacity are derived, which provide fast means to evaluate the system performance. In addition, the channel we assume is shadowed Rician (SR) channel, which is close to the reality. Finally, simulation results are provided to verify the correctness of the analytical results.","PeriodicalId":371691,"journal":{"name":"2016 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123514405","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 : 2016-12-01DOI: 10.1109/ISSPIT.2016.7886045
Ji Wu, Yang Lu, Wei Dai
WiFi signals have been widely used in short-distance wireless communication and thus become a promising option for passive radar applications, where sources of opportunity are exploited in a multi-static system. In the processing of passive radar signals, discrete compressed sensing (CS) techniques have been proved in previous research to be capable of producing better estimation than traditional methods based on correlation and side slope removal. But unstable performance and the need of data-association become remaining problems while the resolution achieved still leaves much to be desired. We introduce an off-grid CS scheme to WiFi-based radar and propose a multi-receiver (SIMO) model, where the positions and speeds of planar objects are directly recovered, to deal with the problems mentioned above, in which case discrete CS requires excessively large space for the storage of the measurement matrix. The simulation result shows its power in overcoming the previous obstacles as well as reaching higher resolution and precision.
{"title":"Off-grid compressed sensing for WiFi-based passive radar","authors":"Ji Wu, Yang Lu, Wei Dai","doi":"10.1109/ISSPIT.2016.7886045","DOIUrl":"https://doi.org/10.1109/ISSPIT.2016.7886045","url":null,"abstract":"WiFi signals have been widely used in short-distance wireless communication and thus become a promising option for passive radar applications, where sources of opportunity are exploited in a multi-static system. In the processing of passive radar signals, discrete compressed sensing (CS) techniques have been proved in previous research to be capable of producing better estimation than traditional methods based on correlation and side slope removal. But unstable performance and the need of data-association become remaining problems while the resolution achieved still leaves much to be desired. We introduce an off-grid CS scheme to WiFi-based radar and propose a multi-receiver (SIMO) model, where the positions and speeds of planar objects are directly recovered, to deal with the problems mentioned above, in which case discrete CS requires excessively large space for the storage of the measurement matrix. The simulation result shows its power in overcoming the previous obstacles as well as reaching higher resolution and precision.","PeriodicalId":371691,"journal":{"name":"2016 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)","volume":"130 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128073325","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 : 2016-12-01DOI: 10.1109/ISSPIT.2016.7886031
Mana Negishi, Y. Mitsukura
In this paper, we aimed to get the trends of the KANSEI, which is alike “how to feel”, values of the memorable TV commercials (CMs) using the electroencephalogram (EEG) while subjects watch TV CMs. KANSEI is Japanese word because of studying at first in Japan. The questionnaire has been used as conventional evaluation method of TV CMs. This method is subjective evaluation, so it is difficult to know the details of situations that affect memory because it cannot get instantaneous evaluation. To solve this problem, we did memory follow-up questionnaire surveys and measured the EEG when watching memorable TV CMs that is objective evaluation using the bio signals. We got KANSEI values from EEG data using “KANSEI Analyzer”. A KANSEI Analyzer is an application which detects subject's degrees of five emotional states: “Like”, “Interest”, “Concentration”, “Calmness”, and “Stress”, by original system constructed by Dentsu ScienceJam Inc‥ The degree of each emotional state is calculated per second, which is represented in percentage (0%: low degree - 100%: high degree). We did carry out two experiments and compared KANSEI values. We performs correlation analysis, and get trends of KANSEI values in watching memorable TV CMs. As a result, we got the trends of KANSEI values when watching memorable TV CMs that “Concentration” and “Stress” values 3∼10% decreased toward end of TV CMs, and went up in last few seconds. Also, “Interest” value increased. Accordingly, we were able to get the trends of the KANSEI values of the memorable TV CMs using the EEG when watching TV CMs.
{"title":"Detection of KANSEI value trends using the electroencephalogram during watching memorable TV commercials","authors":"Mana Negishi, Y. Mitsukura","doi":"10.1109/ISSPIT.2016.7886031","DOIUrl":"https://doi.org/10.1109/ISSPIT.2016.7886031","url":null,"abstract":"In this paper, we aimed to get the trends of the KANSEI, which is alike “how to feel”, values of the memorable TV commercials (CMs) using the electroencephalogram (EEG) while subjects watch TV CMs. KANSEI is Japanese word because of studying at first in Japan. The questionnaire has been used as conventional evaluation method of TV CMs. This method is subjective evaluation, so it is difficult to know the details of situations that affect memory because it cannot get instantaneous evaluation. To solve this problem, we did memory follow-up questionnaire surveys and measured the EEG when watching memorable TV CMs that is objective evaluation using the bio signals. We got KANSEI values from EEG data using “KANSEI Analyzer”. A KANSEI Analyzer is an application which detects subject's degrees of five emotional states: “Like”, “Interest”, “Concentration”, “Calmness”, and “Stress”, by original system constructed by Dentsu ScienceJam Inc‥ The degree of each emotional state is calculated per second, which is represented in percentage (0%: low degree - 100%: high degree). We did carry out two experiments and compared KANSEI values. We performs correlation analysis, and get trends of KANSEI values in watching memorable TV CMs. As a result, we got the trends of KANSEI values when watching memorable TV CMs that “Concentration” and “Stress” values 3∼10% decreased toward end of TV CMs, and went up in last few seconds. Also, “Interest” value increased. Accordingly, we were able to get the trends of the KANSEI values of the memorable TV CMs using the EEG when watching TV CMs.","PeriodicalId":371691,"journal":{"name":"2016 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129010573","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 : 2016-12-01DOI: 10.1109/ISSPIT.2016.7886013
V. Parque, T. Miyashita
Being a significant construct in a wide range of combinatorial problems, the k-subset sum problem (k-SSP) computes k-element subsets, out of an n-element set, satisfying a user-defined aggregation value. In this paper, we formulate the k-subset sum problem as a search (optimization) problem over the space of integers associated with combination elements. And by using rigorous computational experiments using the search space over more than 1014 integer numbers, we show that our approach is effective and efficient: it is feasible to find any combination with a user-defined sum within 104 function evaluations by using a gradient-free optimization algorithm. Our scheme opens the door to further advance the understanding of combinatorial problems by improved/tailored gradient-free optimization algorithms based on enumerative encoding. Also, our approach realizes the practical building block for combinatorial problems in planning and operations research using k-SSP concepts.
{"title":"On k-subset sum using enumerative encoding","authors":"V. Parque, T. Miyashita","doi":"10.1109/ISSPIT.2016.7886013","DOIUrl":"https://doi.org/10.1109/ISSPIT.2016.7886013","url":null,"abstract":"Being a significant construct in a wide range of combinatorial problems, the k-subset sum problem (k-SSP) computes k-element subsets, out of an n-element set, satisfying a user-defined aggregation value. In this paper, we formulate the k-subset sum problem as a search (optimization) problem over the space of integers associated with combination elements. And by using rigorous computational experiments using the search space over more than 1014 integer numbers, we show that our approach is effective and efficient: it is feasible to find any combination with a user-defined sum within 104 function evaluations by using a gradient-free optimization algorithm. Our scheme opens the door to further advance the understanding of combinatorial problems by improved/tailored gradient-free optimization algorithms based on enumerative encoding. Also, our approach realizes the practical building block for combinatorial problems in planning and operations research using k-SSP concepts.","PeriodicalId":371691,"journal":{"name":"2016 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125615881","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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