2016 IEEE 12th International Colloquium on Signal Processing & Its Applications (CSPA)最新文献_第6页

CORDIC-based FFT real-time processing design and FPGA implementation 基于cordic的FFT实时处理设计与FPGA实现

2016 IEEE 12th International Colloquium on Signal Processing & Its Applications (CSPA) Pub Date : 2016-03-04 DOI: 10.1109/CSPA.2016.7515837

Ai-Jun Tang, Yu Li, Fangjian Han, Zhiqiang Zhang

引用次数: 15

Design of fuzzy fractional-order PI+ PD controller 模糊分数阶PI+ PD控制器的设计

2016 IEEE 12th International Colloquium on Signal Processing & Its Applications (CSPA) Pub Date : 2016-03-04 DOI: 10.1109/CSPA.2016.7515841

M. Tajjudin, N. Ishak, M. Rahiman, R. Adnan

引用次数: 3

Extraction method of accompaniment signal using stereo type noise suppression method 伴奏信号的提取方法采用立体声型噪声抑制方法

2016 IEEE 12th International Colloquium on Signal Processing & Its Applications (CSPA) Pub Date : 2016-03-04 DOI: 10.1109/CSPA.2016.7515819

Takahiro Natori, N. Tanabe, T. Furukawa

引用次数: 2

Feature level fusion for biometric verification with two-lead ECG signals 特征级融合的生物特征验证与双导联心电信号

2016 IEEE 12th International Colloquium on Signal Processing & Its Applications (CSPA) Pub Date : 2016-03-04 DOI: 10.1109/CSPA.2016.7515803

Maryamsadat Hejazi, S. Al-Haddad, S. Hashim, A. F. A. Aziz, Y. P. Singh

引用次数: 11

Determining the state of truthfulness and falsehood by analyzing the acquired EEG signals 通过对采集到的脑电信号进行分析，确定真假状态

2016 IEEE 12th International Colloquium on Signal Processing & Its Applications (CSPA) Pub Date : 2016-03-04 DOI: 10.1109/CSPA.2016.7515826

Rumeysa Çakmak, A. Zeki

{"title":"Determining the state of truthfulness and falsehood by analyzing the acquired EEG signals","authors":"Rumeysa Çakmak, A. Zeki","doi":"10.1109/CSPA.2016.7515826","DOIUrl":"https://doi.org/10.1109/CSPA.2016.7515826","url":null,"abstract":"Detection of deception is particular importance for the criminal case and cognitive behaviors of individual. To understanding criminal behavior, extracting the characteristic of brain waves have obviously crucial. According to hypothesis, particularly prefrontal lobes associated with the deception. This paper alleged to understanding the relationship between deception and truth from frontal lobe during some specific tasks by mapping their EEG signals. In the present study, multiplayer neural network are used for bio-signal classification to diversify between patterns of lie and truth types of EEG classes with the accuracy of around 96%. Brain activity have been captured and characterized with EEG by focusing alpha waves. During the test, lie detection identified and especially focus to detect lie in individual subjects, rather than group averages. In this research, the classification methods applied and EEG machine differentiated the specific patterns of brain activity from frontal lobes associated with deception and truth. The responses from the 3 subjects was discriminated correctly with 99%. The ranges of accuracy of test from three subjects was between 88% to 96%, there was an exception in round three with subject three with 46%. While the participants were playing with “Pokemon card”, alpha waves were collected successfully.","PeriodicalId":314829,"journal":{"name":"2016 IEEE 12th International Colloquium on Signal Processing & Its Applications (CSPA)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133158010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Comparison of perturbation signals for ill-conditioned systems and their effectiveness in model-based control 病态系统摄动信号的比较及其在模型控制中的有效性

2016 IEEE 12th International Colloquium on Signal Processing & Its Applications (CSPA) Pub Date : 2016-03-04 DOI: 10.1109/CSPA.2016.7515822

T. Yap, A. H. Tan, W. Tan

引用次数: 1

Prediction of raw broiler shear force using visible and short wave Near Infrared Spectroscopy 利用可见光和短波近红外光谱预测生肉鸡剪切力

2016 IEEE 12th International Colloquium on Signal Processing & Its Applications (CSPA) Pub Date : 2016-03-04 DOI: 10.1109/CSPA.2016.7515852

Rashidah Ghazali, H. A. Rahim

{"title":"Prediction of raw broiler shear force using visible and short wave Near Infrared Spectroscopy","authors":"Rashidah Ghazali, H. A. Rahim","doi":"10.1109/CSPA.2016.7515852","DOIUrl":"https://doi.org/10.1109/CSPA.2016.7515852","url":null,"abstract":"Tenderness is one of the quality that will affect consumer perception in meat. Traditionally, meat quality grading was done destructively by the human graders destructive measurements. Destructive measurement caused less accurate results, time-consuming and costly. Hence, a low cost, fast, reliable and non-destructive technique which is Near-Infrared Spectroscopy (NIRS) is required in order to gain accurate results in tenderness prediction. The combination of visible and shortwave near infrared (VIS-SWNIR) spectrometer and principal component regression (PCR) to assess the quality attribute of raw broiler meat texture (shear force value (kg)) was investigated. Two wavelength regions: visible and shortwave 662- 1005 nm and shortwave 700-1005 nm. Absorbance spectra was pre-processed using the optimal Savitzky-Golay smoothing mode which was the 1st order derivative, 2nd degree polynomial and 31 filter points to remove the baseline shift effect. Potential outliers were identified through externally studentised residual approach. The PCR model were trained with 90 samples in calibration and validated with 44 samples in prediction datasets. From the PCR analysis, correlation coefficient of calibration (RC), the root mean square calibration (RMSEC), correlation coefficient of prediction (RP) and the root mean square prediction (RMSEP) of visible and shortwave (662-1005 nm) with 4 principal components were 0.4645, 0.0898, 0.4231 and 0.0945. The predicted results can be improved by applying the 2nd order derivative and the non-linear model.","PeriodicalId":314829,"journal":{"name":"2016 IEEE 12th International Colloquium on Signal Processing & Its Applications (CSPA)","volume":"138 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114169361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Design of a model-following servo controller by the integral-type state equation 基于积分型状态方程的模型跟随伺服控制器设计

2016 IEEE 12th International Colloquium on Signal Processing & Its Applications (CSPA) Pub Date : 2016-03-04 DOI: 10.1109/CSPA.2016.7515804

S. Inoue, Y. Ishida

引用次数: 1

An automatic fire detection and warning system under home video surveillance 家庭视频监控下的自动火灾探测和报警系统

2016 IEEE 12th International Colloquium on Signal Processing & Its Applications (CSPA) Pub Date : 2016-03-04 DOI: 10.1109/CSPA.2016.7515842

M. Hasan, M. Razzak

引用次数: 17

Construction of predictive models for bicycle riding comfort evaluation using electromyogram and electroencephalogram 基于肌电图和脑电图的自行车骑行舒适性评价预测模型的构建

2016 IEEE 12th International Colloquium on Signal Processing & Its Applications (CSPA) Pub Date : 2016-03-04 DOI: 10.1109/CSPA.2016.7515812

Noriki Toyoshima, S. Kanoga, Y. Mitsukura

引用次数: 1