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Titlebook: Nature Inspired Problem-Solving Methods in Knowledge Engineering; Second International José Mira,José R. álvarez Conference proceedings 200

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41#
發(fā)表于 2025-3-28 18:18:25 | 只看該作者
https://doi.org/10.1007/978-3-540-73055-2Augmented Reality; Fuzzy; Knowledge Engineering; ant colony optimization; artificial intelligence; artifi
42#
發(fā)表于 2025-3-28 18:47:13 | 只看該作者
Performance Monitoring of Closed-Loop Controlled Systems Using dFasArt,system operation states. Digital Signal Processing is used to represent temporal signal with spatial patterns. A neuro-fuzzy scheme (dFasArt) is proposed to classify these patterns, in an on-line way, characterizing the state of controller performance. A real scale plant has been used to carry out several experiments with good results.
43#
發(fā)表于 2025-3-29 01:43:09 | 只看該作者
44#
發(fā)表于 2025-3-29 07:09:55 | 只看該作者
45#
發(fā)表于 2025-3-29 11:09:28 | 只看該作者
0302-9743 Overview: 978-3-540-73054-5978-3-540-73055-2Series ISSN 0302-9743 Series E-ISSN 1611-3349
46#
發(fā)表于 2025-3-29 13:44:18 | 只看該作者
47#
發(fā)表于 2025-3-29 18:16:27 | 只看該作者
HANNA: A Tool for Hardware Prototyping and Benchmarking of ANNs,on platform of an ANN for a given application. This paper describes HANNA, a software tool designed to automate the generation of hardware prototypes of MLP and MLP-like neural networks over FPGA devices. Coupled with traditional Matlab./Simulink. environments the generated model can be synthesized,
48#
發(fā)表于 2025-3-29 22:34:05 | 只看該作者
Improvement of ANNs Performance to Generate Fitting Surfaces for Analog CMOS Circuits,ications are very restrictive, and so, the performance of these networks must be improved. This is the case of analog CMOS circuits, where models created must provide an accuracy which some times is difficult to achieve using classical techniques. In this paper we describe a modelling method for suc
49#
發(fā)表于 2025-3-30 02:23:37 | 只看該作者
Wavelet Network for Nonlinearities Reduction in Multicarrier Systems,r multicarrier systems. Parameters of the proposed network are identified using an hybrid training algorithm, which adapts the linear output parameters using the least square algorithm and the nonlinear parameters of the hidden nodes are trained using the gradient descent algorithm. Computer simulat
50#
發(fā)表于 2025-3-30 05:07:35 | 只看該作者
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