Proceedings of the International Conference on Imaging, Signal Processing and Communication最新文献

Real-time Voice Activity Detector Using Gammatone Filter and Modified Long-Term Signal Variability 实时语音活动检测器使用伽玛酮滤波器和修改的长期信号变异性

Proceedings of the International Conference on Imaging, Signal Processing and Communication Pub Date : 2017-07-26 DOI: 10.1145/3132300.3132320

W. Ong, A. Tan, V. Vengadasalam, C. Tan, T. Ooi

{"title":"Real-time Voice Activity Detector Using Gammatone Filter and Modified Long-Term Signal Variability","authors":"W. Ong, A. Tan, V. Vengadasalam, C. Tan, T. Ooi","doi":"10.1145/3132300.3132320","DOIUrl":"https://doi.org/10.1145/3132300.3132320","url":null,"abstract":"In this paper, a real-time robust voice activity detector (VAD) is proposed. The proposed VAD adopts the gammatone filter and modify the existing long-term signal variability (LTSV) measure, i.e. known as GMLTSV in short. The proposed VAD is an improved version of existing VAD which used gammatone filter and entropy. The LTSV measure is modified to adapt to the amplitude envelopes extracted using gammatone filter by swapping entropy and variance used in LTSV measure to reduce noise effect in the extracted temporal envelopes and improve discriminative power of the extracted feature. The proposed algorithm also implements an adaptive threshold that is computed using a nonlinear filter to track short-term trend of the extracted feature in real-time. The proposed VAD using GMLTSV feature is tested against clean speech signals from TIMIT test corpus which are degraded at SNR ranged from -10dB to 20dB by non-stationary noise, eg. airport noise, babble noise, exhibition noise from Aurora-2 database, and stationary noise, eg. additive white Gaussian noise. Based on the evaluation, it is proven that the proposed GMLTSV-based VAD is robust in speech and non-speech detection even at low signal-to-noise ratio (SNR) and outperformed other existing voice activity detectors which are compared in the evaluation. The proposed VAD achieved satisfactory accuracy when compared to the impractical single frequency filtering based VAD while implementing real-time scheme for practical application.","PeriodicalId":448865,"journal":{"name":"Proceedings of the International Conference on Imaging, Signal Processing and Communication","volume":"221 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134127703","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

Optimal Electroencephalogram Signals Denoising using Hybrid β-Hill Climbing Algorithm and Wavelet Transform 基于混合β-爬坡算法和小波变换的脑电图信号优化去噪

Proceedings of the International Conference on Imaging, Signal Processing and Communication Pub Date : 2017-07-26 DOI: 10.1145/3132300.3132314

Zaid Abdi Alkareem Alyasseri, A. Khader, M. Al-Betar

{"title":"Optimal Electroencephalogram Signals Denoising using Hybrid β-Hill Climbing Algorithm and Wavelet Transform","authors":"Zaid Abdi Alkareem Alyasseri, A. Khader, M. Al-Betar","doi":"10.1145/3132300.3132314","DOIUrl":"https://doi.org/10.1145/3132300.3132314","url":null,"abstract":"In this paper, hybridization between β-hill climbing algorithm and wavelet transform (WT) are proposed for Electro Encephalo Gram (EEG) signal denoising problem. EEG is a graphical measurement for the brain electrical activity which is recording from the scalp. It represents the voltage fluctuations resulting from ionic current flows within the neurons of the brain. During recording time, there are several artifacts noises can corrupt the original EEG signals such as eye blink, eye movements, muscles activity, and interference of power line. Therefore, the EEG signals should be processed to remove these noises obtaining the efficient EEG features. Several techniques have been proposed for EEG noises reduction in which one of these techniques is an EEG signal denoising using wavelet transforms (WT). Selecting wavelet parameters is a challenging task that is usually performed based on empirical evidence or experience. Therefore, β-hill climbing is proposed to find optimal wavelet parameters for EEG signal denoising that can obtain the minimum mean square error (MSE) between the original and denoised EEG signals. The proposed method was tested using a standard EEG dataset which is established by Kiern and Aunon. The proposed hybrid method was also evaluated using five criteria which are: Signal-to-Noise-Ration (SNR), SNR improvement, Mean Square Error (MSE), Root Mean Square Error (RMSE), and percentage root mean square difference (PRD). Finally, βHCWT compares with WT without βHC to show the effect of β-hill climbing on WT performance. The proposed method reveals an outstanding noise removal performance for non-stationary signals.","PeriodicalId":448865,"journal":{"name":"Proceedings of the International Conference on Imaging, Signal Processing and Communication","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124768248","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: 16

Wireless Sensor Network Based Outdoor and Indoor Positioning System (WOIPS) Featured with IoT 基于无线传感器网络的室内外定位系统(WOIPS)

Proceedings of the International Conference on Imaging, Signal Processing and Communication Pub Date : 2017-07-26 DOI: 10.1145/3132300.3132332

A. Al-nahari, Noor Azurati Ahmad, Y. Yusof

引用次数: 2

Shortwave-Position-Resource Scheduling Method Based on Signal Quality Estimation via Neural Network and Dynamic Weight Adjustment 基于神经网络信号质量估计和动态权值调整的短波位置资源调度方法

Proceedings of the International Conference on Imaging, Signal Processing and Communication Pub Date : 2017-07-26 DOI: 10.1145/3132300.3132325

Lijia Zhang, Jing Zhang, Xiaoyi Zhang

{"title":"Shortwave-Position-Resource Scheduling Method Based on Signal Quality Estimation via Neural Network and Dynamic Weight Adjustment","authors":"Lijia Zhang, Jing Zhang, Xiaoyi Zhang","doi":"10.1145/3132300.3132325","DOIUrl":"https://doi.org/10.1145/3132300.3132325","url":null,"abstract":"The manual expert scheduling, currently utilized in shortwave position system, is unable to satisfy the modern scenario of intensive tasks and deficient resources, thus resulting in the low position accuracy. To address the problem, we propose a shortwave-position-resource scheduling method based on Back Propagating Neural Network (BPNN) and Dynamic Weight Adjustment (DWA). Firstly, we conceive a basic centralized optimization model for problem formulation, constructing an objective function consisted by Geometrical Dilution of Precision (GDOP) and signal quality via linear weight summation. Furthermore, we study the dynamic adjustment strategy of weights. With weights updated according to the gradients of factors, the objective function inclines to the factor of better performance during iterations, thus leading to a better optimization searching ability. Moreover, by introducing the Bayesian Regulation (BR) and Levenberg-Marquardt (LM) algorithm, we make an improvement on the generalization performance of BPNN, then achieving the signal quality estimation in the shortwave channel. Simulations indicate that the proposed method obtains an excellent robustness in scenes of different tasks number. When compared with other scheduling methods, the proposed method can effectively enhance the location accuracy. Experiments also show that the timeliness of the method is relatively low and needs further improvement.","PeriodicalId":448865,"journal":{"name":"Proceedings of the International Conference on Imaging, Signal Processing and Communication","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122585980","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

Synthesizable Assertion in Hardware and Software Development 硬件和软件开发中的可综合断言

Proceedings of the International Conference on Imaging, Signal Processing and Communication Pub Date : 2017-07-26 DOI: 10.1145/3132300.3132317

Ooi Ruey Hock, Z. Aziz, Jwing Teh

{"title":"Synthesizable Assertion in Hardware and Software Development","authors":"Ooi Ruey Hock, Z. Aziz, Jwing Teh","doi":"10.1145/3132300.3132317","DOIUrl":"https://doi.org/10.1145/3132300.3132317","url":null,"abstract":"Assertion Based Validation (ABV) is an approach in which the design intent is captured in an executable form where all the out of range and missing intent intents will trigger an error which indicates the fall-outs. By using these assertions can enable early detection of very basic software and hardware bugs in the design. System Verilog is a hardware description language that combine with verification and commonly used as assertion language with its powerful assertion function embedded in the language itself. However not all system verilog language can be synthesize into hardware component and because of the limitation, it only use in software simulation phase of a design cycle. The approach to enable the ABV module in system verilog format to be synthesized into a portion of the hardware is the intent of this paper. It defines the synthesizable building blocks of the assertion modules. This can utilized by both hardware and software development in pre-silicon stage through reconfigurable hardware or Field Programmable Gate Array (FPGA). In hardware debug, the synthesized assertions will point to the area of failure, reducing the scope of debug. In software development, the synthesized assertions will point to invalid configurations of hardware registers. The assertions will be synthesized into a separate hardware block which is programmed into a reconfigurable hardware or FPGA together with the Design-Under-Test (DUT). The assertion validation hardware block consists of a 'Detection and Distribution' block and a series of 'Property Tracking' block to track the multiple events separately. If all separate events are met but the expected scenario is not met, a register bit will be set for this assertion point to signify failure. Final assertion results will be written to memory on the reconfigurable hardware or FGPA. The purpose of this paper is to identify the common assertion function that widely use in hardware design and synthesis of these assertion properties from SVA to verilog structure.","PeriodicalId":448865,"journal":{"name":"Proceedings of the International Conference on Imaging, Signal Processing and Communication","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115388451","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

CMOS Voltage Controlled Oscillator (VCO) with frequency stability for extended operating temperature range 具有频率稳定的CMOS压控振荡器(VCO)，可扩展工作温度范围

Proceedings of the International Conference on Imaging, Signal Processing and Communication Pub Date : 2017-07-26 DOI: 10.1145/3132300.3132321

S. S. Hamid, R. A. Zawawi, S. Mohd, Nuha A. Rhaffor, Z. Aziz

引用次数: 0

Locating Success Within A Geographic Information System 在地理信息系统中定位成功

Proceedings of the International Conference on Imaging, Signal Processing and Communication Pub Date : 2017-07-26 DOI: 10.1145/3132300.3132305

Ir. Fazilah Mat Yatim, Z. Majid, S. Amerudin

引用次数: 0

Coupling Material Flow Analysis (MFA) and Geographic Information System (GIS) Methodologies for Screening Flow and Emission of Biomass Energy in the Agricultural System 耦合物质流分析(MFA)和地理信息系统(GIS)方法筛选农业系统中生物质能的流动和排放

Proceedings of the International Conference on Imaging, Signal Processing and Communication Pub Date : 2017-07-26 DOI: 10.1145/3132300.3132336

L. Ghani, N. Mahmood, N. Ali

{"title":"Coupling Material Flow Analysis (MFA) and Geographic Information System (GIS) Methodologies for Screening Flow and Emission of Biomass Energy in the Agricultural System","authors":"L. Ghani, N. Mahmood, N. Ali","doi":"10.1145/3132300.3132336","DOIUrl":"https://doi.org/10.1145/3132300.3132336","url":null,"abstract":"In the agriculture sector, sustainability retention of biomass management is a complicated issue, especially without increasing potential damage towards the environment. This study aims to develop an integrated MAGI conceptual framework using Material Flow Analysis (MFA) and Geographic Information System (GIS) to measure and display spatial biomass energy flow in an agricultural system in Kuala Terengganu. The scope for this research consists of two dominant pools namely crop production and livestock production. By integrating the MFA inventory data, biomass energy model for the year 2016 has been developed based on early results obtained. The study found that the major portion of the energy is focused in crop production, which is 56% higher than livestock production. The findings also estimated 35% agricultural waste recovery potential It seems that the integration of MFA and GIS is an interesting, ideal, and powerful combination of decision making tool because it is able to provide information and firm decision on the development of bioenergy management system and can be used to implement strategies to reduce energy use and pollutants released into the environment.","PeriodicalId":448865,"journal":{"name":"Proceedings of the International Conference on Imaging, Signal Processing and Communication","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129367204","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: 4

Transformer Oil Degradation Monitoring With Chromatically Analysed Optical Fluorescence 用色谱分析光学荧光法监测变压器油的降解

Proceedings of the International Conference on Imaging, Signal Processing and Communication Pub Date : 2017-07-26 DOI: 10.1145/3132300.3132329

C. K. Lo, H. Looe, A. Sufian, G. Jones, J. W. Spencer

引用次数: 1

Electroencephalogram Signals Denoising using Various Mother Wavelet Functions: A Comparative Analysis 不同母小波函数对脑电图信号去噪的比较分析

Proceedings of the International Conference on Imaging, Signal Processing and Communication Pub Date : 2017-07-26 DOI: 10.1145/3132300.3132313

Zaid Abdi Alkareem Alyasseri, A. Khader, M. Al-Betar

{"title":"Electroencephalogram Signals Denoising using Various Mother Wavelet Functions: A Comparative Analysis","authors":"Zaid Abdi Alkareem Alyasseri, A. Khader, M. Al-Betar","doi":"10.1145/3132300.3132313","DOIUrl":"https://doi.org/10.1145/3132300.3132313","url":null,"abstract":"In this paper, various mother wavelet functions are proposed for ElectroEncephaloGram (EEG) signal denoising problem. EEG is a graphical measuring of the brain electrical activity which is recording from the scalp. It represents the voltage fluctuations resulting from ionic current flows within the neurons of the brain. During recording time, there are several artifacts noises can corrupt the original EEG signal such as eye blink, eye movements, muscles activity, and interference of power line. Therefore, the EEG signals should be processed to remove these noises obtaining the efficient EEG features. Several techniques have been proposed for EEG noises reduction in which one of these techniques is an EEG signal denoising using wavelet transform (WT). Selection efficient mother wavelet function (Φ) is considered as a critical parameter in wavelet denoising for non-stationary signal because it will affect the denoised signal. In this paper, four mother wavelet functions (i.e, db4, sym7, bior3.9, and coif3) are tested using standard EEG dataset which is established by Kiern and Aunon. The selected mother wavelet functions evaluation using five criteria which are: Signal-to-Noise-Ration (SNR), SNR improvement, Mean Square Error (MSE), Root Mean Square Error (RMSE), and percentage root mean square difference (PRD. Finally, the coif3 achieves the efficient EEG signal denoising for Power Line Noise (PLN) and Electromyogram (EMG) noise. In addition, sym7 obtained the best result with White Gaussian Noise (WGN).","PeriodicalId":448865,"journal":{"name":"Proceedings of the International Conference on Imaging, Signal Processing and Communication","volume":"193 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120929001","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: 32