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learned-patterns
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Pattern of Learning of Technological Capabilities in Knowledge Based Firms: Cases in Electronics Equipment Industry
, M.Sc. Thesis Sharif University of Technology ; Souzanchi Kashani, Ebrahim (Supervisor)
Abstract
Knowledge based companies have a very important role in progress toward an economy based on knowledge and technology. One of the most important issues about these companies is pattern of Learning Technological capabilities. This issue and the question about the focus of companies about acquire and development of technological capabilities are subjects that have instructive points for both minor and major scales, for companies themselves, and public directing and investing. In this paper pattern of learning of technological capabilities are reviewed for four Knowledge based companies in electronics equipment industry, also the time needed for acquiring levels of technological capabilities for...
A fuzzy learning model for retrieving and learning information in visual working brain memory mechanism
, Article 2017 25th Iranian Conference on Electrical Engineering, ICEE 2017, 2 May 2017 through 4 May 2017 ; 2017 , Pages 61-64 ; 9781509059638 (ISBN) ; Bagheri Shouraki, S ; Jahed, M ; Sharif University of Technology
Abstract
In this investigation, the idea of Visual Working Memory (VWM) mechanism modeling based on versatile fuzzy method; Active Learning method, is presented. Visual information process; retrieving and learning rely on the use of Ink Drop Spread (IDS) and Center of Gravity (COG) as spatial density convergence operators. IDS modeling is characterized by processing that uses intuitive pattern information instead of complex formulas, and it is capable of stable and fast convergence. Furthermore, because it approves that distortion in retrieving irrelative data is adaptive to avoid storing lots of repetitive external information in daily visualization. Subsequently, this distortion is analyzed via two...
Support vector data description for spoken digit recognition
, Article BIOSIGNALS 2012 - Proceedings of the International Conference on Bio-Inspired Systems and Signal Processing ; 2012 , Pages 32-37 ; 9789898425898 (ISBN) ; Ghasemi, A ; Tavanaei, M ; Sameti, H ; Manzuri, M. T ; Inst. Syst. Technol. Inf., Control Commun. (INSTICC) ; Sharif University of Technology
2012
Abstract
A classifier based on Support Vector Data Description (SVDD) is proposed for spoken digit recognition. We use the Mel Frequency Discrete Wavelet Coefficients (MFDWC) and the Mel Frequency cepstral Coefficients (MFCC) as the feature vectors. The proposed classifier is compared to the HMM and results are promising and we show the HMM and SVDD classifiers have equal accuracy rates. The performance of the proposed features and SVDD classifier with several kernel functions are evaluated and compared in clean and noisy speech. Because of multi resolution and localization of the Wavelet Transform (WT) and using SVDD, experiments on the spoken digit recognition systems based on MFDWC features and...
Effective page recommendation algorithms based on distributed learning automata
, Article 4th International Multi-Conference on Computing in the Global Information Technology, ICCGI 2009, 23 August 2009 through 29 August 2009, Cannes, La Bocca ; 2009 , Pages 41-46 ; 9780769537511 (ISBN) ; Rahbar, A ; Mahdavi, M ; Sharif University of Technology
Abstract
Different efforts have been done to address the problem of information overload on the Internet. Recommender systems aim at directing users through this information space, toward the resources that best meet their needs and interests by extracting knowledge from the previous users' interactions. In this paper, we propose an algorithm to solve the web page recommendation problem. In our algorithm, we use distributed learning automata to learn the behavior of previous users' and recommend pages to the current user based on learned pattern. Our experiments on real data set show that the proposed algorithm performs better than the other algorithms that we compared to and, at the same time, it is...