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Recursive algorithms for discrete cosine transform

Recursive algorithms for discrete cosine transform

引用

3rd international conference on signal processing (ICSP 96)

作者： Zhao, ZJ Qian, HS Hangzhou Institute of Electronics Engineering Hangzhou China

ISBN: (纸本)7505338900

In this paper a recursive algorithm with regular structure is first presented for computing the discrete cosine transform(DCT-II), it requires no data shifts, the multiplication coefficients can be generated by a simple recursion. Then the recursive algorithms for DCT-I and DCT-IV are presented. These algorithms have no value stable problem, which complexity is the same as that of Reference[3] and [7], and these algorithms are very useful for practice.

关键词： discrete cosine transforms signal processing fast algorithm

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Optimization Research on Radar signal processing Technology Based on MTI-MTD 3

Optimization Research on Radar Signal Processing Technology ...

引用

2023 IEEE 3rd international conference on data Science and Computer Application, ICDSCA 2023

作者： Mao, Mingzheng Han, Xinrui Beijing Institute of Technology School of Information and Electronics Beijing100081 China

ISBN: (纸本)9798350341546

Due to the continuous development of radar signal processing technology, the MTI-MTD (moving target detection) technology is deeply studied in this paper. This article introduces the principles and properties of MTI and MTD filter banks and analyzes their advantages in clutter suppression, signal-to-noise ratio improvement, and target velocity measurement. Therefore, a radar signal processing system based on MTI-MTD technology, including an acquisition, preprocessing, and target recognition module, is designed. First, the acquisition module receives the radar echo signal and performs analog-to-digital conversion. Second, the preprocessing module is responsible for some operations on the echo signal, such as MTI filtering and Keystone distance migration correction. Third, the target recognition module is responsible for MTD filtering of the preprocessed signal and uses the neural network model to classify and locate the target. Through the verification of three sets of experimental data, the effectiveness and feasibility of this method are high. In addition, we compare it with the traditional method. The experiment results show that the radar signal processing method based on MTI-MTD technology can detect moving targets at various distances, speeds, and signal-to-noise ratios. It improves the ability of radar signal processing technology to detect moving targets in clutter. © 2023 IEEE.

关键词： Keystone distance migration correction MTD filter banks MTI filter Neural network Radar signal processing

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A Computationally Efficient EEG signals Segmentation and De-noising Based on an Adaptive Rate Acquisition and processing 3

A Computationally Efficient EEG Signals Segmentation and De-...

引用

IEEE 3rd international conference on signal and Image processing (ICSIP)

作者： Qaisar, Saeed Mian Effat Univ Elect & Comp Engn Dept Jeddah Saudi Arabia

ISBN: (纸本)9781538663967

The segmentation and de-noising are basic operations, required in every signal processing and classification system. The classical segmentation and de-noising approaches are time-invariant. Consequently, it results in the post processing of unnecessary information and causes an increase in the system processing activity and power consumption. In this context, an efficient event-driven segmentation and de-noising technique is proposed. It is founded on the principles of level crossing and activity selection. Therefore, it can adapt its sampling frequency, segmentation window length and position along with the filter order by analyzing the input signal local characteristics. As a result, the computational complexity and the power consumption of the proposed system is reduced compared to the counter ones. The suggested system performance is compared with the classical one. It is done for the case of a 118 channels Electroencephalogram (EEG) signals. Results show a noticeable compression gain with an effective adaptation of the de-noising filters order. It promises a significant computational gain, transmission data rate reduction and power consumption reduction of the proposed technique, compared to the counter ones. It shows that the proposed solution is an attractive candidate to embed in the new generation EEG devices.

关键词： electroencephalogram adaptive rate signal acquisition activity selection data compression adaptive rate filtering nearest neighbor interpolation

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Characteristics of video data for signal analysis

Characteristics of video data for signal analysis

引用

3rd international conference on signal processing (ICSP 96)

作者： Sridharan, PN Raman, S Tata Consultancy Services Madras India

ISBN: (纸本)7505338900

Video data is complex, unstructured and voluminous unlike conventional text data. For providing effective retrieval facilities, video data needs to be stored in a database with an appropriate data structure. Hence, identifying the required information units and formulating a data structure have become the fundamental tasks. data mining methods analyze data for extracting patterns. In this paper, we elaborate the characteristics of video data which must play a significant role in the development of the data mining algorithm. We have discussed the characteristics of video data under three classes, namely, dominant, native and assigned which have influenced us in arriving at a scheme for analysis.

关键词： Video signal processing

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Research on Information processing System Under Computer Artificial Intelligence Big data Technology 3

Research on Information Processing System Under Computer Art...

引用

3rd international signal processing, Communications and Engineering Management conference, ISPCEM 2023

作者： Peng, Lei Fu, Qiang Li, Zhi Lin, Musong Qian, Yihua Electric Power Research Institute of Guangdong Power Grid Co. Ltd. Guangdong Key Laboratory of Electric Power Equipment Reliability Guangzhou China

ISBN: (纸本)9798350307023

In this paper, a virtual view image post-processing method using background information is proposed. Firstly, a depth-based method is used to deal with overlapping between two images. Secondly, the artifacts of the left and right virtual view are located by the motion direction of the observation point, and the artifacts are eliminated by the background pixels in the supplementary view Angle. Then the background image is filled with holes and combined with the foreground image to form a virtual perspective image. The experimental results show that the peak signal noise of this method is 0.6357 dB better than that of the traditional method. Experiments show that the method proposed in this paper can improve the rendering effect significantly. © 2023 IEEE.

关键词： Big data

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Artificial Intelligence Enhanced signal processing in Low-Profile Wearable Wideband Antenna for Future 5G Wireless communications 3

Artificial Intelligence Enhanced Signal Processing in Low-Pr...

引用

3rd international conference on Artificial Intelligence and signal processing, AISP 2023

作者： Rentapalli, Vanitha Rani Roy, Bappadittya VIT-AP University School of Electronics Engineering Andhra Pradesh Amaravati India

ISBN: (纸本)9798350320749

Artificial intelligence-based communication is the newtechnological tool, that is going to apply for signal processing techniques gives the main consociate to implement any type of applications. The antenna that needs to be designed for 5G wireless networks need to attain broad concepts over broadband artificial technology and its structural formations for all kinds of wearable antenna developments. Moreover, the artificial intelligent technology was recently admitted in communications to work with real modern technology concepts to resolve the unknown and hidden data related to innovative communication systems. AI could apparently handle all kinds of scientific signal processing problems in a data determined manner, to enhance the inherent characteristics to extract the real data. Hence the AI is particularly suitable for signal processing communications over advanced technical networks, hardware impairments and other dynamic transmissions. In this paper we are going to present over the key features of artificial intelligence sensing techniques, and how the intelligent processing features helps us to design the 5G wireless technology for advanced wearable antenna designs. The simulation results depict that how the 5G technology gives its performance characteristics over the data transmission. © 2023 IEEE.

关键词： Artificial intelligence

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Churn Prediction analysis Using Various Clustering Algorithms in KNIME Analytics Platform 3

Churn Prediction analysis Using Various Clustering Algorithm...

引用

3rd IEEE international conference on Sensing, signal processing and Security (ICSSS)

作者： Franciska, I. Swaminathan, B. Rajalakshmi Engn Coll Comp Sci & Engn ME Thandalam India

ISBN: (纸本)9781509049295

In data mining techniques, Clustering is a performed by grouping objects based on similarity of its characteristics to provide patterns and knowledge of given user data. Different types of clustering algorithms called partitioning, hierarchical and grid based clustering methods. Here k-means clustering, k-medoids clustering, Hierarchical clustering, DBSCAN and Fuzzy c means clustering. Clustering algorithms are used for customer churn analysis;one of the important reasons is that the cost of increasing a new customer is much higher than retaining an existing customer by using customer churn analysis. Initially KNIME analytics platform is used to analyse and visualization of data and later it is used to create model, rules and interactive views of data.

关键词： data Mining Clustering KNIME Analytics Platform

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Exploration and Mining of Multipurpose Cooperative Business data 2019

Exploration and Mining of Multipurpose Cooperative Business ...

引用

3rd international conference on Digital signal processing (ICDSP) / 2nd international conference on Computer Graphics and Virtuality (ICCGV)

作者： Trinidad, Joventino T., Jr. Abra State Inst Sci & Technol Main Campus Lagangilang Abra Philippines

ISBN: (纸本)9781450362047

In the Philippines, cooperative transition to becoming technology-driven actors in the development sector by initiating the development of ICT solutions specifically catered to cooperatives and their operations. Without data mining behind crucial decision making in a cooperative management, the fate of these cooperatives may be likened to banks on the verge of bankruptcy. Therefore, cooperative basic business data mining to discover patterns and trends helpful in decision making is being introduced in this study. All districts than can be equated to municipalities are well represented by members of the multipurpose cooperative. There is an equally efficient collection measures of the cooperative management on equity and Mutual Aid System (MAS).

关键词： Exploration data Mining Multipurpose Cooperatives Business data

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Customer Churn Prediction using Neural Networks and SMOTE-ENN for data Sampling 3

Customer Churn Prediction using Neural Networks and SMOTE-EN...

引用

3rd international conference on Artificial Intelligence and signal processing, AISP 2023

作者： Gore, Shubham Chibber, Yuvraj Bhasin, Manan Mehta, Shyam Suchitra, S. SRM Institute of Science & Technology Kattankulathur Data Science and Business Systems Chennai India

ISBN: (纸本)9798350320749

To survive in the telecommunications industry's severe competition and to keep existing loyal customers, predicting prospective churn consumers has become a critical task that may be accomplished with efficient predictive models. For many years, churn studies have been utilized to boost profitability and make customer-company relationships more sustainable. Customer churn is estimated using a multi-layer perceptron prediction model based on ANN. Furthermore, the suggested model manages the data's uneven class distribution using an advanced oversampling strategy called SMOTE-ENN based on K-Nearest Neighbors. The models accuracy was compared with and without SMOTE-ENN and the model using SMOTE-ENN showed better results. © 2023 IEEE.

关键词： Telecommunication industry

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Mining Technology of Big data Trusted Sharing in Supply Chain 3

Mining Technology of Big Data Trusted Sharing in Supply Chai...

引用

3rd international signal processing, Communications and Engineering Management conference, ISPCEM 2023

作者： Yan, Wan Tianjin University of Technology Tianjin China

ISBN: (纸本)9798350307023

In view of the low input and output efficiency of traditional supply chain sharing mining technology, a trusted sharing mining technology of supply chain big data based on improved data envelope analysis algorithm was proposed. The supply chain trust evaluation method based on improved DEA algorithm is adopted, and the evaluation results are stored in the form of data set. DEA algorithm is used to optimize the input and output efficiency of supply chain sharing, and genetic algorithm is combined to avoid the local optimal problem of DEA algorithm. The supply chain big data streaming method is adopted to process the data set data, and the data is provided to each subject in the shared information publishing layer with certification qualification to access and use, and the trusted sharing mining of supply chain big data is realized. The experimental results show that the technology has excellent big data sharing mining effect, can effectively adjust the supply chain input and output, and improve the overall performance of the supply chain. © 2023 IEEE.

关键词： Supply chains

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