Titlebook: Evolving Connectionist Systems; Methods and Applicat Nikola Kasabov Book 20031st edition Springer-Verlag London 2003 automata.bioinformatic

可卡

Alexandra Hall,Georgios A. Antonopoulosrmation are integrated. The framework allows for learning, adaptation, knowledge discovery and decision making. An application of the framework is a person identification system in which face and voice recognition are combined in one system. Experiments are performed using visual and auditory dynami

注意

安撫

大喘氣

Perspectives in Neural Computinghttp://image.papertrans.cn/e/image/318101.jpg

RENAL

https://doi.org/10.1007/978-3-030-86219-0nnectionist systems is also presented. Major features of evolving connectionist systems such as on-line learning, adaptive learning, life-long learning, supervised/ unsupervised/ reinforcement learning, knowledge-based learning, statistical learning, open structure and others are defined and illustrated.

EXTOL

harbinger

會議

打火石

On-Line Adaptive Speech Recognitionme common tools for communication and information processing. This chapter is concerned with methods and systems for adaptive speech recognition. An adaptive system can learn spoken phonemes, words and phrases. New words, pronunciations and languages can be introduced to the system in an incremental, adaptive way.

Peak-Bone-Mass

Epiloguewell help to create evolving intelligent machines that would learn and improve in a lifelong mode through active interaction with humans, with other systems, and with the environment we live in. This can result in enhancing our knowledge in different domains, making our lives easier and more enjoyable.