Titlebook: Sequence Learning; Paradigms, Algorithm Ron Sun,C. Lee Giles Book 2001 Springer-Verlag Berlin Heidelberg 2001 algorithms.behavior.biologica

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書目名稱Sequence Learning影響因子(影響力)




書目名稱Sequence Learning影響因子(影響力)學(xué)科排名




書目名稱Sequence Learning網(wǎng)絡(luò)公開度




書目名稱Sequence Learning網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Sequence Learning被引頻次




書目名稱Sequence Learning被引頻次學(xué)科排名




書目名稱Sequence Learning年度引用




書目名稱Sequence Learning年度引用學(xué)科排名




書目名稱Sequence Learning讀者反饋




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Time in Connectionist Modelsconnectionist models have appeared and constitute a continuously growing research field. The purpose of this chapter is to present the main aspects of this research area and to review the key connectionist architectures that have been designed for solving temporal problems.

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Book 2001veryday skills to complex problem solving. Sequence learning is an important component of learning in many tasks and application fields: planning, reasoning, robotics natural language processing, speech recognition, adaptive control, time series prediction, financial engineering, DNA sequencing, and

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Attentive Learning of Sequential Handwriting Movements: A Neural Network Model a series of distinct segments that may be quite irregular both in space and time, but a practiced movement can be made smoothly, with a continuous, often bell-shaped, velocity profile. How does learning of sequential movements transform reactive imitation into predictive, automatic performance?

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