2017 IEEE 13th International Colloquium on Signal Processing & its Applications (CSPA)最新文献_第4页

Prediction of glucose concentration using near infrared light and adaptive linear neuron 利用近红外光和自适应线性神经元预测葡萄糖浓度

2017 IEEE 13th International Colloquium on Signal Processing & its Applications (CSPA) Pub Date : 2017-03-01 DOI: 10.1109/CSPA.2017.8064920

K. Chia, Nur Aisyah Syafinaz Suarin, S. Fuzi

引用次数: 4

Pattern classifier of chemical compounds in different qualities of agarwood oil parameter using scale conjugate gradient algorithm in MLP 用尺度共轭梯度算法对沉香油参数中不同品质的化合物进行模式分类

2017 IEEE 13th International Colloquium on Signal Processing & its Applications (CSPA) Pub Date : 2017-03-01 DOI: 10.1109/CSPA.2017.8064917

N. Zubir, M. A. Abas, N. Ismail, N. A. Ali, M. Rahiman, N. K. Mun, M. Taib, N. Saiful

引用次数: 11

An improved method for OMP-based algorithm; using fusing strategy 基于omp算法的改进方法使用融合策略

2017 IEEE 13th International Colloquium on Signal Processing & its Applications (CSPA) Pub Date : 2017-03-01 DOI: 10.1109/CSPA.2017.8064951

Yi Xu, Guiling Sun, Tianyu Geng, Zhouzhou Li

引用次数: 4

Time and frequency domain features of EMG signal during Islamic prayer (Salat) 伊斯兰礼拜时肌电信号的时频域特征

2017 IEEE 13th International Colloquium on Signal Processing & its Applications (CSPA) Pub Date : 2017-03-01 DOI: 10.1109/CSPA.2017.8064939

N. Ahamed, Tasriva Sikandar, M. Rabbi, K. Ghazali

引用次数: 6

Multiple Input Single Output (MISO) ARX and ARMAX model of flood prediction system: Case study Pahang 多输入单输出(MISO)洪水预报系统的ARX和ARMAX模型:以彭亨州为例

2017 IEEE 13th International Colloquium on Signal Processing & its Applications (CSPA) Pub Date : 2017-03-01 DOI: 10.1109/CSPA.2017.8064947

F. Ruslan, Khadijah Haron, A. Samad, R. Adnan

{"title":"Multiple Input Single Output (MISO) ARX and ARMAX model of flood prediction system: Case study Pahang","authors":"F. Ruslan, Khadijah Haron, A. Samad, R. Adnan","doi":"10.1109/CSPA.2017.8064947","DOIUrl":"https://doi.org/10.1109/CSPA.2017.8064947","url":null,"abstract":"Year end usually would see many states in Malaysia would probably hits by severe floods due to Monsoon rain especially in the east coast. Many peoples suffered properties damages and economic losses. Thus, an accurate flood water level prediction model is required as an alarm system that would warn the affected area and residence to prepare for evacuation due to the upcoming severe flood. This paper compared the prediction performances of a developed flood prediction models that were designed using Multiple-Input Single-Output (MISO) Auto regressive with Exogenous Input (ARX) and MISO Auto regressive Moving Average with Exogenous Input (ARMAX) structure. The models were designed using Matlab System Identification toolbox of parametric model. The location for the case of study was at Pahang River, Temerloh, Pahang with four upstream stations and one downstream station or observed location. The data used were obtained from the Malaysian Department of Drainage and Irrigation. Simulation results showed that the prediction performance of flood prediction model designed by ARMAX structure showed better Best Fit value and smaller rmse values as compared to the model designed using ARX structure.","PeriodicalId":445522,"journal":{"name":"2017 IEEE 13th International Colloquium on Signal Processing & its Applications (CSPA)","volume":"35 11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114275881","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: 12

Angle of arrival estimation by using stereo ultrasonic technique for local positioning system 基于立体超声技术的局部定位系统到达角估计

2017 IEEE 13th International Colloquium on Signal Processing & its Applications (CSPA) Pub Date : 2017-03-01 DOI: 10.1109/CSPA.2017.8064934

Woottichai Nonsakhoo, Piyanat Sirisawat, Saiyan Saiyod, N. Benjamas

引用次数: 7

Real-time feedback for children's pre-writing activities using haptic technology 使用触觉技术对儿童写作前活动进行实时反馈

2017 IEEE 13th International Colloquium on Signal Processing & its Applications (CSPA) Pub Date : 2017-03-01 DOI: 10.1109/CSPA.2017.8064942

Muhammad Amir Azwan Mohamad Aminordin, Noor Latiffah Adam, N. Diah

引用次数: 0

Classification of human breathing task based on electromyography signal of respiratory muscles 基于呼吸肌肌电信号的呼吸任务分类

2017 IEEE 13th International Colloquium on Signal Processing & its Applications (CSPA) Pub Date : 2017-03-01 DOI: 10.1109/CSPA.2017.8064950

A. Morali, A. Abdullah, Z. Zakaria, N. A. Rahim, V. Vijean, S. K. Nataraj

{"title":"Classification of human breathing task based on electromyography signal of respiratory muscles","authors":"A. Morali, A. Abdullah, Z. Zakaria, N. A. Rahim, V. Vijean, S. K. Nataraj","doi":"10.1109/CSPA.2017.8064950","DOIUrl":"https://doi.org/10.1109/CSPA.2017.8064950","url":null,"abstract":"Breathing is one of the human physiological activities that catch the interest of researchers especially in the area of medical diagnosis and human physiological performance. Apart from conventional measurement using intake or outflow of air, breathing characteristics could also be assessed through human respiratory muscles with the analysis on Electromyography (EMG) signal. In this paper, EMG signal of human breathing is acquired from four respiratory muscles i.e. sternocleidomastoid, scalene, intercostal muscle and diaphragm while subjects perform four different breathing tasks. The aim is to classify EMG features from the muscles into the four breathing tasks. Classification is done using Feedforward Multi-layer Perceptron Artificial Neural Network (MLPANN). Four features are derived from the EMG data i.e. root-mean-square (RMS), zero crossing (ZC), mean frequency (MNF) and mean frequency power (MP). Classification is performed to compare the accuracy result of input vector from the four features of EMG and three combination set of these features using i) four data segmentation frame sizes and ii) six number of hidden neurons. The result of data classification shows highest accuracy when all feature sets is used as input to MLPANN with segmentation frame size of 1000 ms and number of hidden neurons of 60. Classifation accuracy obtained is 59.52%.","PeriodicalId":445522,"journal":{"name":"2017 IEEE 13th International Colloquium on Signal Processing & its Applications (CSPA)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127524269","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

Walsh transform with moving average filtering for data compression in wireless sensor networks 移动平均滤波的沃尔什变换在无线传感器网络中的数据压缩

2017 IEEE 13th International Colloquium on Signal Processing & its Applications (CSPA) Pub Date : 2017-03-01 DOI: 10.1109/CSPA.2017.8064964

Mohamed Elsayed, M. Mahmuddin, A. Badawy, Tarek M. Elfouly, Amr M. Mohamed, K. Abualsaud

引用次数: 11

Landscape analysis system using 3D stereoscopic for drone 景观分析系统采用三维立体为无人机

2017 IEEE 13th International Colloquium on Signal Processing & its Applications (CSPA) Pub Date : 2017-03-01 DOI: 10.1109/CSPA.2017.8064935

Noppakorn Thanomsieng, Nattaphong Boonruam, Piyanat Sirisawat, Woottichai Nonsakhoo, Saiyan Saiyod

引用次数: 2