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1. There are no standards for learning algorithms or for training networks.
2. An unsupervised learning algorithm might emphasize cooperation among clusters of processing elements.
3. Weights, summing and transfer functions, and learning algorithms all rely heavily on mathematics.
4. A learning algorithm of procedure neural networks is proposed.
5. An average reward reinforcement learning algorithm for control Markov chains is presented.
6. Immune algorithm is a kind of intelligent learning algorithm which simulates the biology immunity systems.
6. Sentencedict.com try its best to gather and create good sentences.
7. This paper presents a learning algorithm based on artificial immune which has the characteristics of recognition variable and self-adjustment.
8. In the application studies of ADP methods, a learning algorithm solving the queueing system optimization problem and a direct adaptive optimal control method are suggested.
9. The rank learning algorithm based on the decision tree is able to process categorical data and select relative features.
10. In this paper, a hierarchical reinforcement learning algorithm is investigated for Markov Decision Process with average reward.
11. In this paper, a hierarchical reinforcement learning algorithm is investigated for Markov decision process with average cost.
12. As for it, by improving learning algorithm of traditional RBF neural network, a new dynamic cluster-based self-generated method for hidden layer nodes is proposed.
13. Furthermore, the exploring study of the reinforcement learning algorithm adopted in the MA collaborative decision was offered.
14. We then describe an entropy penalized AMS learning algorithm on Gaussian mixture.
15. How the interconnection weights are changed is the function of the learning algorithm.
16. Their goal is to advance both hardware implementation and learning algorithms.
17. To the problems higher rate of false retrieval in anomaly detection system due to the uncertainty of intrusion, this paper presents an Anomaly Detection Model Based on Q- Learning Algorithm (QLADM).
18. Based on the above - mentioned result a fast pseudo - inverse matrix learning algorithm is obtained for the CNN.
19. In this paper(sentencedict.com), we proposed a parallel BP neural network learning algorithm with the support of PC cluster under the circumstance of PVM(Parallel Virtual Machine).
20. The Counterpropagation Network(CPN) can be applied to image compression as a vector quantizer. However, the CPN learning algorithm has two obvious disadvantages in codebook designing.
21. A fire signal detection model based on fuzzy neural - network and its learning algorithm are this paper.
22. For the above reasons, the extended Kalman filter is proposed as RBF learning algorithm, and the biradial function is used in hidden layer.
23. In this paper we proposed an adaptive equalizer based on complex Hebbian-type learning algorithm.
24. Derived from the standpoint of minimum error parameter estimation, a fast learning algorithm for solving interconnection matrix W of the network is of fast convergence property.
25. To solve the problem of slow computation speed and low image matching accuracy, a new approach to image matching using population-based increased learning algorithm (PBIL) was proposed.
26. Then, we proved that the same condition is sufficient for the robustness of the proposed learning algorithm against state disturbance, output measurement noise, and initialization error.
27. The paper first presents an objective model of task scheduling, and then based on the analysis of Q learning algorithm, the Markov decision process description of the scheduling problem is given.
28. The experiments on Maze problem show that COSTRLA has better performance than the classical reinforcement learning algorithm for solving goal state problem.
29. This tracker uses a modified radial basis function (RBF) neural network which incorporates a learning algorithm for tracking the noisy chaotic signal under parameter variation.
30. Swarm-robot simulation system is a digital system that is used for the demonstration of the control architecture, cooperative control, learning algorithm of swarm-robot system.
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