Recent developments of the syntactic pattern recognition model based on quasi-context sensitive languages

Jurek, Janusz

doi:10.1016/j.patrec.2004.09.056

Cited by 25 publications

(6 citation statements)

References 5 publications

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“…. , −1 }, and is the number of target patterns [42][43][44][45]. If it is assumed that there are obtained observation sequences = { − +1 , − +2 , .…”

Section: Pattern Recognition In Sa-ann Cognition Frameworkmentioning

confidence: 99%

A SA‐ANN‐Based Modeling Method for Human Cognition Mechanism and the PSACO Cognition Algorithm

Chen

Tan

2018

Complexity

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Artificial neural networks (ANNs) are the important approaches for researching human cognition process. However, current ANNsbased cognition methods cannot address the problems of complex information understanding and fault-tolerant learning. Here we present a modeling method for cognition mechanism based on a simulated annealing-artificial neural network (SA-ANN). Firstly, the relationship between SA processing procedure and cognition knowledge evolution is analyzed, and a SA-ANN-based inference model is set up. Then, based on the inference model, a Powell SA with combinatorial optimization (PSACO) algorithm is proposed to improve the clustering efficiency and recognition accuracy for the cognition process. Finally, three groups of numerical instances for knowledge clustering are provided, and three comparative experiments are performed by self-developed cognition software. The simulated results show that the proposed method can increase the convergence rate by more than 20%, compared with the back-propagation (BP), SA, and restricted Boltzmann machines based extreme learning machine (RBM-ELM) algorithms. The comparative cognition experiments prove that the method can obtain better performances of information understanding and fault-tolerant learning, and the cognition accuracies for original sample, damaged sample, and transformed sample can reach 99.6%, 99.2%, and 97.1%, respectively.

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“…. , −1 }, and is the number of target patterns [42][43][44][45]. If it is assumed that there are obtained observation sequences = { − +1 , − +2 , .…”

Section: Pattern Recognition In Sa-ann Cognition Frameworkmentioning

confidence: 99%

A SA‐ANN‐Based Modeling Method for Human Cognition Mechanism and the PSACO Cognition Algorithm

Chen

Tan

2018

Complexity

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“…The most important decision concerning the implementation of the agent has been the choice of GDPLL(k) grammars [8] as a formal string grammar which is used to store knowledge about a component behaviour and to construct a control table for the parser. The definition of GDPLL(k) grammar and its brief characteristics are included in next section.…”

Section: Fig 1 a General Scheme Of A Syntactic Pattern Recognition-ba...mentioning

confidence: 99%

Grammatical Inference as a Tool for Constructing Self-learning Syntactic Pattern Recognition-Based Agents

Jurek

2008

Computational Science – ICCS 2008

Self Cite

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Syntactic pattern recognition-based agents have been proven to be a useful tool for constructing real-time process control intelligent systems. In the paper the problem of self-learning schemes in the agents is discussed. Learning capabilities are very important if practical applications of the agents are considered, since the agents should be able to accumulate knowledge about the environment and flexible react to the changes in the environment. As it is shown in the paper, the learning scheme in the agents can be based on a suitable grammatical inference algorithm.

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“…They are powerful enough to describe the syntax of programming languages [1] (almost all programming languages are defined via CFGs) and simple enough to allow the construction of efficient parsing algorithms. Additionally, general context-free methods are exploited today in various application domains, such as speech recognition, natural or programming language processing and image analysis, syntactic filtering, artificial intelligence [2,[4][5][6][7][8][9]. The large amount of data manipulated by those methods and today's requirement of conforming to very strict real-time constraints, turns the implementation of CFG-parsers that are optimized for performance more useful and imperative than ever.…”

Section: Introductionmentioning

confidence: 99%

Efficient reconfigurable embedded parsers

Pavlatos

Dimopoulos

Koulouris

et al. 2009

Computer Languages, Systems & Structures

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Recent developments of the syntactic pattern recognition model based on quasi-context sensitive languages

Cited by 25 publications

References 5 publications

A SA‐ANN‐Based Modeling Method for Human Cognition Mechanism and the PSACO Cognition Algorithm

A SA‐ANN‐Based Modeling Method for Human Cognition Mechanism and the PSACO Cognition Algorithm

Grammatical Inference as a Tool for Constructing Self-learning Syntactic Pattern Recognition-Based Agents

Efficient reconfigurable embedded parsers

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