FPGA-based approximate calculation system of General Vector Machine

Yang, Xuhui; Zhou, Qing; Wang, Jinqiang; Feng, Fang; Zhou, Rui; Li, Kuan‐Ching

doi:10.1016/j.mejo.2019.02.018

Cited by 3 publications

(3 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Credit system is a teaching management system based on the completion of students' credits to measure students' learning and carry out related management work. [4] Credit system includes a lot of basic system contents, mainly: course selection system, course system, credit management, flexible learning system, tutorial system, grade point system [5] . In the modern apprenticeship teaching mode, the cooperation between schools and enterprises is highlighted, and education, training and employment are organically combined.…”

Section: Diversified Assessment and Evaluation Based On Credit Systemmentioning

confidence: 99%

Research on Training Mode of the Application-oriented Undergraduates Based on Modern Apprenticeship ——Taking Financial Management as an Example

Wang,

Zhang

2023

Proceedings of the 4th International Conference on Modern Education and Information Management, ICMEIM 2023, September 8–10, 20

View full text Add to dashboard Cite

At present, the cultivation of application-oriented undergraduate students lacks the professional training of working technics. Compared with academics-oriented undergraduates, there is no obvious difference. And student training does not highlight application-oriented characteristics. Modern apprenticeships promote the integration of education, training and employment, with a focus on enhancing students' professional practice skills. Based on this, this paper constructs a student-training mode that meets the needs of corporations. This paper also creates a curriculum system based on the "role theory". Meanwhile, this paper implements the "order-based" training method, and establishes a multiple assessment and evaluation method based on the "credit system". Taking the undergraduate degree of financial management as an example, the four dimensions of this teaching mode are verified in practice to explore its practical application effect. Through a questionnaire of 142 people, most of the teacher and students gave a positive assessment on this mode.

show abstract

Section: Diversified Assessment and Evaluation Based On Credit Systemmentioning

confidence: 99%

Research on Training Mode of the Application-oriented Undergraduates Based on Modern Apprenticeship ——Taking Financial Management as an Example

Wang,

Zhang

2023

Proceedings of the 4th International Conference on Modern Education and Information Management, ICMEIM 2023, September 8–10, 20

View full text Add to dashboard Cite

show abstract

“…Nanjing University, Beijing University of Aeronautics and Astronautics, and Aviation Industry Corporation have successively developed a number of testing tools and testing systems, whose main role is to cover embedded systems. After that, the employees of China State Shipbuilding Corporation conducted in-depth research on the GUI automated testing technology of embedded software and proposed a nonintrusive embedded GUI automated testing framework [8,9]. Others proposed testing based on the characteristics of ship embedded software [10].…”

Section: Related Workmentioning

confidence: 99%

Design and Implementation of Embedded Real-Time English Speech Recognition System Based on Big Data Analysis

Jin

Tsai

2021

Mathematical Problems in Engineering

View full text Add to dashboard Cite

This article uses Field Programmable Gate Array (FPGA) as a carrier and uses IP core to form a System on Programmable Chip (SOPC) English speech recognition system. The SOPC system uses a modular hardware system design method. Except for the independent development of the hardware acceleration module and its control module, the other modules are implemented by software or IP provided by Xilinx development tools. Hardware acceleration IP adopts a top-down design method, provides parallel operation of multiple operation components, and uses pipeline technology, which speeds up data operation, so that only one operation cycle is required to obtain an operation result. In terms of recognition algorithm, a more effective training algorithm is proposed, Genetic Continuous Hidden Markov Model (GA_CHMM), which uses genetic algorithm to directly train CHMM model. It is to find the optimal model by encoding the parameter values of the CHMM and performing operations such as selection, crossover, and mutation according to the fitness function. The optimal parameter value after decoding corresponds to the CHMM model, and then the English speech recognition is performed through the CHMM algorithm. This algorithm can save a lot of training time, thereby improving the recognition rate and speed. This paper studies the optimization of embedded system software. By studying the fixed-point software algorithm and the optimization of system storage space, the real-time response speed of the system has been reduced from about 10 seconds to an average of 220 milliseconds. Through the optimization of the CHMM algorithm, the real-time performance of the system is improved again, and the average time to complete the recognition is significantly shortened. At the same time, the system can achieve a recognition rate of over 90% when the English speech vocabulary is less than 200.

show abstract

“…The results demonstrated that deeper MCNN performed better than shallow MCNN [34]. Yang et al introduced a GVM approximate calculation system based on field programmable gate array, which can effectively accelerate the calculation of GVM [35].…”

Section: B Alo and Gvmmentioning

confidence: 99%

Using Cost-Sensitive Learning and Feature Selection Algorithms to Improve the Performance of Imbalanced Classification

Feng

Shen

et al. 2020

IEEE Access

Self Cite

View full text Add to dashboard Cite

Imbalanced data problem is widely present in network intrusion detection, spam filtering, biomedical engineering, finance, science, being a challenge in many real-life data-intensive applications. Classifier bias occurs when traditional classification algorithms are used to deal with imbalanced data. As already known, the General Vector Machine (GVM) algorithm has good generalization ability, though it does not work well for the imbalanced classification. Additionally, the state-of-the-art Binary Ant Lion Optimizer (BALO) algorithm has high exploitability and fast convergence rate. Based on these facts, we have proposed in this paper a Cost-sensitive Feature selection General Vector Machine (CFGVM) algorithm based on GVM and BALO algorithms to tackle the imbalanced classification problem, delivering different cost weights to different classes of samples. In our method, the BALO algorithm determines the cost weights and extract more significant features to improve the classification performance. Experiments conducted on eleven imbalanced data sets have shown that the CFGVM algorithm significantly improves the classification performance of minority class samples. By comparing with similar algorithms and stateof-the-art algorithms, the proposed algorithm significantly outperforms in performance and produces better classification results. INDEX TERMS Imbalanced data, cost-sensitive, general vector machine, binary ant lion optimizer.

show abstract

FPGA-based approximate calculation system of General Vector Machine

Cited by 3 publications

References 13 publications

Research on Training Mode of the Application-oriented Undergraduates Based on Modern Apprenticeship ——Taking Financial Management as an Example

Research on Training Mode of the Application-oriented Undergraduates Based on Modern Apprenticeship ——Taking Financial Management as an Example

Design and Implementation of Embedded Real-Time English Speech Recognition System Based on Big Data Analysis

Using Cost-Sensitive Learning and Feature Selection Algorithms to Improve the Performance of Imbalanced Classification

Contact Info

Product

Resources

About