愚笨
发表于 2025-3-28 17:50:07
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radiograph
发表于 2025-3-28 22:03:52
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enormous
发表于 2025-3-29 02:01:32
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高度
发表于 2025-3-29 03:56:24
Conference proceedings 2015f cognition. The second volume deals with bioinspired computation in artificial systems; topics alluded are bio-inspired circuits and mechanisms, bioinspired programming strategies, and bioinspired engineering AI&KE..
athlete’s-foot
发表于 2025-3-29 07:40:25
0302-9743 l foundations and approaches to the study of cognition. The second volume deals with bioinspired computation in artificial systems; topics alluded are bio-inspired circuits and mechanisms, bioinspired programming strategies, and bioinspired engineering AI&KE..978-3-319-18832-4978-3-319-18833-1Series ISSN 0302-9743 Series E-ISSN 1611-3349
时代错误
发表于 2025-3-29 15:12:40
https://doi.org/10.1007/978-3-642-92913-7the errors made in the odometry in unusual friction conditions by means of a multiple model particle filter (MMPF) based hybridization. In concrete, we focus on slides since these appear more often in road vehicles. The theoretical contributions, along with the good results obtained in real trials are presented in the paper.
Pepsin
发表于 2025-3-29 17:31:04
A Multiple-Model Particle Filter Based Method for Slide Detection and Compensation in Road Vehiclesthe errors made in the odometry in unusual friction conditions by means of a multiple model particle filter (MMPF) based hybridization. In concrete, we focus on slides since these appear more often in road vehicles. The theoretical contributions, along with the good results obtained in real trials are presented in the paper.
地牢
发表于 2025-3-29 22:51:54
Evolution of Synaptic Delay Based Neural Controllers for Implementing Central Pattern Generators introl. We compared the results against continuous time recurrent neural networks, one of the neural models most used as CPG, when proprioceptive information is used to provide fault tolerance for the required behavior.
amphibian
发表于 2025-3-30 01:09:11
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obstruct
发表于 2025-3-30 06:01:21
Evolving Cellular Automata to Segment Hyperspectral Images Using Low Dimensional Images for Trainin are constructed on-line according to a set of parameters that define the type of segmentation the user wants. A series of segmentation experiments over real hyperspectral images are presented to show this adaptability and how the performance of the algorithm improves over other state of the art approaches found in the literature on the subject.