Bayesian signal processing: A practical guide to particle filtering design and performance

2021 ◽  
Vol 149 (4) ◽  
pp. A84-A84
Author(s):  
James V. Candy
Keyword(s):  
Signal Processing ◽  
Particle Filtering ◽  
Practical Guide ◽  
Bayesian Signal Processing ◽  
And Performance

About quality of dissertations, or this strange GOST

2021 ◽  
pp. 65-75
Author(s):  
Yu.V. Kazakov ◽  
Keyword(s):  
Graduate Students ◽  
System Approach ◽  
Scientific Methodology ◽  
Structural Elements ◽  
Academic Degree ◽  
Practical Guide ◽  
Classical Methodology ◽  
And Performance

Examined is relevance of a subject of work is caused by the continuing deterioration of dissertation works. Therefore, article purpose is to define the system reason of deterioration of training of the top skills by the analysis of contents and structure of theses. The main shortcomings of dissertations, and understanding of their structural elements by applicants of an academic degree by communication with them in the course of preparation and carrying out preliminary protection of these were analyzed. Results of the analysis were compared to requirements of classical methodology and to interpretation of these requirements in the methodical managements and in publications. The essential system reason of decline in quality of dissertation works is in their traditional unsystematic structure, whith investigation withdrawal from scientific methodology and particular leveling of motivation to the analysis of a condition of a question and the received results of researches and also to system approach to the thesis, need of strengthening of methodological training of graduate students according to the uniform nation-wide program providing system approach to the organization of researches for all scientific specialties, and processing’s of the “Thesis and Abstract of the Thesis” standard according to classical requirements of scientific methodology and the system approach to dissertation work Is shown. The system scheme of the thesis, which can make a manual basis is the practical guide to organization and performance of dissertation work for training of graduate students and applicants is offered.

scholarly journals VLSI ARCHITECTURE OF PARALLEL MULTIPLIER– ACCUMULATOR BASED ON RADIX-2 MODIFIED BOOTH ALGORITHM

2012 ◽  
pp. 40-46
Author(s):  
Mr.M.V. Sathish ◽  
Mrs. Sailaja
Keyword(s):  
Signal Processing ◽  
High Speed ◽  
High Performance ◽  
Vlsi Architecture ◽  
Clock Frequency ◽  
Parallel Multiplier ◽  
Hybrid Type ◽  
Standard Design ◽  
Overall Performance ◽  
And Performance

A new architecture of multiplier-andaccumulator (MAC) for high-speed arithmetic. By combining multiplication with accumulation and devising a hybrid type of carry save adder (CSA), the performance was improved. Since the accumulator that has the largest delay in MAC was merged into CSA, the overall performance was elevated. The proposing method CSA tree uses 1’s-complement-based radix-2 modified Booth’s algorithm (MBA) and has the modified array for the sign extension in order to increase the bit density of the operands. The proposed MAC showed the superior properties to the standard design in many ways and performance twice as much as the previous research in the similar clock frequency. We expect that the proposed MAC can be adapted to various fields requiring high performance such as the signal processing areas.

scholarly journals Data Association Methods via Video Signal Processing in Imperfect Tracking Scenarios: A Review and Evaluation

2020 ◽  
Vol 2020 ◽  
pp. 1-26
Author(s):  
Hui Li ◽  
Yapeng Liu ◽  
Wenzhong Lin ◽  
Lingwei Xu ◽  
Junyin Wang
Keyword(s):  
Signal Processing ◽  
Deep Learning ◽  
Data Association ◽  
Evaluation Criteria ◽  
Video Signal ◽  
Video Signal Processing ◽  
Video Signals ◽  
And Performance ◽  
Multiobject Tracking ◽  
Made In

In 5G scenarios, there are a large number of video signals that need to be processed. Multiobject tracking is one of the main directions in video signal processing. Data association is a very important link in tracking algorithms. Complexity and efficiency of association method have a direct impact on the performance of multiobject tracking. Breakthroughs have been made in data association methods based on deep learning, and the performance has been greatly improved compared with traditional methods. However, there is a lack of overviews about data association methods. Therefore, this article first analyzes characteristics and performance of three traditional data association methods and then focuses on data association methods based on deep learning, which is divided into different deep network structures: SOT methods, end-to-end methods, and Wasserstein metric methods. The performance of each tracking method is compared and analyzed. Finally, it summarizes the current common datasets and evaluation criteria for multiobject tracking and discusses challenges and development trends of data association technology and data association methods which ensure robust and real time need to be continuously improved.

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