Artificial Neural Networks and Machine Learning – ICANN by Marcel A. J. van Gerven, Eric Maris (auth.), Timo Honkela,

By Marcel A. J. van Gerven, Eric Maris (auth.), Timo Honkela, Włodzisław Duch, Mark Girolami, Samuel Kaski (eds.)

This quantity set (LNCS 6791 and LNCS 6792) constitutes the refereed court cases of the 21th foreign convention on synthetic Neural Networks, ICANN 2011, held in Espoo, Finland, in June 2011. The 106 revised complete or poster papers provided have been rigorously reviewed and chosen from quite a few submissions. ICANN 2011 had simple tracks: brain-inspired computing and computer studying study, with robust cross-disciplinary interactions and applications.

Show description

Read or Download Artificial Neural Networks and Machine Learning – ICANN 2011: 21st International Conference on Artificial Neural Networks, Espoo, Finland, June 14-17, 2011, Proceedings, Part II PDF

Best networks books

Computer Networks (4th Edition) - Problem Solutions

Whole recommendations for laptop Networks (4th version) by way of Andrew Tanenbaum.

Advances in Neural Networks - ISNN 2010: 7th International Symposium on Neural Networks, ISNN 2010, Shanghai, China, June 6-9, 2010, Proceedings, Part I

This publication and its sister quantity gather refereed papers awarded on the seventh Inter- tional Symposium on Neural Networks (ISNN 2010), held in Shanghai, China, June 6-9, 2010. development at the good fortune of the former six successive ISNN symposiums, ISNN has develop into a well-established sequence of well known and top quality meetings on neural computation and its functions.

Sensor Networks and Configuration: Fundamentals, Standards, Platforms, and Applications

Advances in networking impact many forms of tracking and regulate platforms within the such a lot dramatic method. Sensor community and configuration falls lower than the class of recent networking structures. instant Sensor community (WSN) has emerged and caters to the necessity for real-world functions. technique and layout of WSN represents a wide study subject with purposes in lots of sectors comparable to undefined, domestic, computing, agriculture, atmosphere, etc, in response to the adoption of primary rules and the cutting-edge expertise.

Additional info for Artificial Neural Networks and Machine Learning – ICANN 2011: 21st International Conference on Artificial Neural Networks, Espoo, Finland, June 14-17, 2011, Proceedings, Part II

Sample text

Including background; this pre-training does not teach the model to distinguish between foreground and background in the training images). For highly structured images the background models were sometimes not sufficiently powerful so that part of the background was assigned to the foreground even after consolidation of the foreground model. This does not completely prohibit learning of the foreground model but leads to a noisy final model. e. 3), which can be incorporated into the Gibbs sampling scheme by modifying equations (3-5).

C Springer-Verlag Berlin Heidelberg 2011 A Distributed Behavioral Model Using Neural Fields 33 results from combination of every agent’s steering behaviors. e. stay close to its neighbors (cohesion), avoid collisions with them (separation) and move in their average direction (alignment) (Fig. 1). The global stimulus is designed by defining the relevance of each behavior relatively to the actual situation. We also consider obstacle avoidance with the highest priority among other stimuli. The control design will be discussed in theoretical terms, supported by simulation results.

5. (c) shows how the contribution of all stimuli provide the appropriate heading directions, which permits to avoid the obstacle. After passing the obstacle the stimulus of obstacle avoidance is removed, and the group continues its movement by combining the three flock behaviors. The global path is illustrated in Fig. 5. (g). 8 0 (a) Phase 1: Cohesion 10 20 30 t [steps] 40 50 60 (b) Phase 1: Headings vs. 5 −1 0 (c) Phase 2: Separation 10 20 30 40 t [steps] 50 60 70 80 (d) Phase 2: Headings vs. 8 0 10 20 30 40 50 60 70 80 t [steps] (e) Phase 3: Alignment (f) Phase 3: Headings vs.

Download PDF sample

Rated 4.56 of 5 – based on 40 votes