2014 11th International Computer Conference on Wavelet Actiev Media Technology and Information Processing(ICCWAMTIP)最新文献_第4页

Vision prehension with CBIR for cloud robo 基于CBIR的云机器人视觉抓取

2014 11th International Computer Conference on Wavelet Actiev Media Technology and Information Processing(ICCWAMTIP) Pub Date : 2014-12-01 DOI: 10.1109/ICCWAMTIP.2014.7073411

Asif Khan, S. Deep, Jian-ping Li, K. Kumar, R. Shaikh, Faraz Hasan

{"title":"Vision prehension with CBIR for cloud robo","authors":"Asif Khan, S. Deep, Jian-ping Li, K. Kumar, R. Shaikh, Faraz Hasan","doi":"10.1109/ICCWAMTIP.2014.7073411","DOIUrl":"https://doi.org/10.1109/ICCWAMTIP.2014.7073411","url":null,"abstract":"Content Based Image Retrieval is very hottest research area in computer vision and image processing. To perceive arbitrary natural scene from complex environment is a challenging issue in visual imaging and processing research area. Neural Network is a grid of “neuron like” nodes, in this paper we follow towards Neural Network (NN), is committed to contributing a new technical concept for the scene understanding and recognition by consolidating new intellectual visual features into the scene expression, which can be very crucial and provide cognitive intelligence to cloud robot. Inspired by Artificial Neural Network intelligence due to its dynamic nature, we make use of the attributes of the Gabor filter and Laplacian of Gaussian filter which is to be akin to robot visual perception, and apply the wavelet transform to inspect a new approach in complex environment natural scene perception and understanding for virtual phenomena. Through the study of Neural Network, the perception ability of the natural scene image from complex environment for cloud robot is enhanced with the integration of cognitive visual features and the scene expression.","PeriodicalId":211273,"journal":{"name":"2014 11th International Computer Conference on Wavelet Actiev Media Technology and Information Processing(ICCWAMTIP)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128107946","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: 8

A tracking method for GPS L2C signal based on the joint using of data and pilot channels 一种基于数据和导频信道联合利用的GPS L2C信号跟踪方法

2014 11th International Computer Conference on Wavelet Actiev Media Technology and Information Processing(ICCWAMTIP) Pub Date : 2014-12-01 DOI: 10.1109/ICCWAMTIP.2014.7073354

Yucheng Liu, Hong Li, X. Cui, Mingquan Lu

{"title":"A tracking method for GPS L2C signal based on the joint using of data and pilot channels","authors":"Yucheng Liu, Hong Li, X. Cui, Mingquan Lu","doi":"10.1109/ICCWAMTIP.2014.7073354","DOIUrl":"https://doi.org/10.1109/ICCWAMTIP.2014.7073354","url":null,"abstract":"GPS L2C signal is one of the modernized GPS civilian signals. With respect to GPS L1 C/A signal, L2C signal is more robust in harsh environment, since its tracking threshold would be lower by taking the advantage of new designed pilot channel. Up to now, some of current tracking methods are only based on the pilot channel or data channel of L2C signal and discard the other, which results in 50% power loss. Other methods are based on the joint tracking of the outputs of data and pilot channels' discriminators, which needs more additional computation resources and the integration time of tracking is limited by data. In this paper, a new method based on joint tracking of data and pilot channels but not discriminators is proposed. We know the navigation data of GPS signal, mainly consisted of ephemeris and almanac, are continuously and repeatedly broadcast. So the navigation data of GPS signal are predicable. Based on this, the proposed method removes the navigation data of data channel through a new designed navigation data predication module, before coherently combines the integration results of data and pilot channel. Then, the coherent integration result has both the energy of data channel and pilot channel. Compared with the previous methods, the proposed method has no power loss and it doesn't need additional computation resource. Furthermore, the integration time will not be limited by navigation data since they have been predictably removed and much better tracking performance is expected. Theoretical and simulation results demonstrated the results.","PeriodicalId":211273,"journal":{"name":"2014 11th International Computer Conference on Wavelet Actiev Media Technology and Information Processing(ICCWAMTIP)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129205818","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: 2

Research on the quantitative analysis of near infrared spectroscopy of astragaloside based on artificial neural network and wavelet transform 基于人工神经网络和小波变换的黄芪甲苷近红外光谱定量分析研究

2014 11th International Computer Conference on Wavelet Actiev Media Technology and Information Processing(ICCWAMTIP) Pub Date : 2014-12-01 DOI: 10.1109/ICCWAMTIP.2014.7073440

Zhang Yong, Y. Hua

{"title":"Research on the quantitative analysis of near infrared spectroscopy of astragaloside based on artificial neural network and wavelet transform","authors":"Zhang Yong, Y. Hua","doi":"10.1109/ICCWAMTIP.2014.7073440","DOIUrl":"https://doi.org/10.1109/ICCWAMTIP.2014.7073440","url":null,"abstract":"With rapidly analysis, no pollution, no damage, simple operation, low analysis cost, environmental protection and many other advantages, the near infrared spectroscopy (NIR) analysis has made breakthrough progress in the Chinese medicine field. In this paper, the near infrared spectrometry of extract of two kinds of astragalus is determined. Wavelet transform is used to compress the spectral variables, and the quantitative analysis models are carried on using artificial neural network technology in order to analyze the astragaloside content of extract of two kinds of astragalus. The simulation results show that, the prediction decision coefficient(R2) is 0.9863, the average relative error is 0.0354, the root mean square error of Cross-Validation(RMSECV) is 0.0258 in the astragalus extract samples (the ratio of material to liquid 1:2), and the predictive decision coefficient is 0.9798, the average relative error is 0.0425, and the root mean square error of Cross-Validation is 0.0301 in the astragalus extract samples (the ratio of material to liquid 1:5). The evaluation model can meet the need of practical application, and provide technical support for quantitative analysis to extract of astragalus and analysis of near infrared spectroscopy in traditional Chinese medicinal materials.","PeriodicalId":211273,"journal":{"name":"2014 11th International Computer Conference on Wavelet Actiev Media Technology and Information Processing(ICCWAMTIP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128573016","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

Application on stock price prediction of Elman neural networks based on principal component analysis method 基于主成分分析法的Elman神经网络在股价预测中的应用

2014 11th International Computer Conference on Wavelet Actiev Media Technology and Information Processing(ICCWAMTIP) Pub Date : 2014-12-01 DOI: 10.1109/ICCWAMTIP.2014.7073438

Hongyan Shi, Xiaowei Liu

{"title":"Application on stock price prediction of Elman neural networks based on principal component analysis method","authors":"Hongyan Shi, Xiaowei Liu","doi":"10.1109/ICCWAMTIP.2014.7073438","DOIUrl":"https://doi.org/10.1109/ICCWAMTIP.2014.7073438","url":null,"abstract":"Study on the prediction of stock price has great theoretical significance and application value. Traditional stock forecasting methods cannot fit and analysis highly nonlinear, multi-factors of stock market well, there are problems such as the prediction accuracy is not high, the slow training speed etc. In order to improve the accuracy of stock price forecasting, this paper proposes a prediction method of Elman neural network model based on principal component analysis method. In order to better compare results, establish structure same BP network and Elman network, forecast for stock data; then using principal component analysis filter factors of significant effect on stock prices, Elman neural network model based on principal component analysis method, and compared with single Elman network and BP networks prediction results. Result shows BP network convergence is relatively slow, train for a long time, and could converge to a local minimum; Elman network training time is short, the error bars for smoother and more stable performance; Elman neural network model based on principal component analysis with higher accuracy, faster network speeds.","PeriodicalId":211273,"journal":{"name":"2014 11th International Computer Conference on Wavelet Actiev Media Technology and Information Processing(ICCWAMTIP)","volume":"597 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116259882","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: 8

Fully homomorphic encryption application in cloud computing 全同态加密在云计算中的应用

2014 11th International Computer Conference on Wavelet Actiev Media Technology and Information Processing(ICCWAMTIP) Pub Date : 2014-12-01 DOI: 10.1109/ICCWAMTIP.2014.7073452

Baohua Chen, Na Zhao

引用次数: 9

Research on information system attribute set information granules based on functional dependency 基于功能依赖的信息系统属性集信息颗粒研究

2014 11th International Computer Conference on Wavelet Actiev Media Technology and Information Processing(ICCWAMTIP) Pub Date : 2014-12-01 DOI: 10.1109/ICCWAMTIP.2014.7073362

Yanbin Hao, Xiao Guo, Naiding Yang

引用次数: 2

Design and realization of visual wireless autonomous lawn mower based on machine vision 基于机器视觉的视觉无线自主割草机的设计与实现

2014 11th International Computer Conference on Wavelet Actiev Media Technology and Information Processing(ICCWAMTIP) Pub Date : 2014-12-01 DOI: 10.1109/ICCWAMTIP.2014.7073425

Hengtao Liu, Zhugang Yuan, Zhe Su

引用次数: 1

Identifying and ranking influential spreaders in complex networks 识别和排序复杂网络中有影响力的传播者

2014 11th International Computer Conference on Wavelet Actiev Media Technology and Information Processing(ICCWAMTIP) Pub Date : 2014-12-01 DOI: 10.1109/ICCWAMTIP.2014.7073434

Zong-Wen Liang, Jian-ping Li

引用次数: 6

Parameters estimation algorithm for the exponential signal by the interpolated all-phase DFT approach 基于插值全相位DFT方法的指数信号参数估计算法

2014 11th International Computer Conference on Wavelet Actiev Media Technology and Information Processing(ICCWAMTIP) Pub Date : 2014-12-01 DOI: 10.1109/ICCWAMTIP.2014.7073356

Qian Wang, Xiao Yan, Kaiyu Qin

引用次数: 2

Overcomplete dictionary based denoising and signal detection for drilling fluid pulse communication 基于过完备字典的钻井液脉冲通信去噪与信号检测

2014 11th International Computer Conference on Wavelet Actiev Media Technology and Information Processing(ICCWAMTIP) Pub Date : 2014-12-01 DOI: 10.1109/ICCWAMTIP.2014.7073431

Zhongwei Li, Chunlei Wu, Xuerong Cui

引用次数: 1