By Ishwar K. Sethi
With the growing to be complexity of development popularity similar difficulties being solved utilizing synthetic Neural Networks, many ANN researchers are grappling with layout concerns resembling the scale of the community, the variety of education styles, and function evaluation and limits. those researchers are constantly rediscovering that many studying techniques lack the scaling estate; the techniques easily fail, or yield unsatisfactory effects whilst utilized to difficulties of larger dimension. Phenomena like those are very commonplace to researchers in statistical trend acceptance (SPR), the place the curse of dimensionality is a well known drawback. concerns with regards to the educational and attempt pattern sizes, characteristic house dimensionality, and the discriminatory energy of other classifier kinds have all been commonly studied within the SPR literature. apparently even though that many ANN researchers taking a look at trend popularity difficulties should not conscious of the binds among their box and SPR, and are as a result not able to effectively make the most paintings that has already been performed in SPR. equally, many development acceptance and desktop imaginative and prescient researchers do not understand the potential for the ANN method of resolve difficulties corresponding to function extraction, segmentation, and item popularity. the current quantity is designed as a contribution to the larger interplay among the ANN and SPR study groups"
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Additional info for Artificial neural networks and statistical pattern recognition: old and new connections
This work was supported by European Regional Development Fund under the project CEBIA-Tech No. 0089. References 1. : Investigation on evolutionary optimization of chaos control. Chaos, Solitons & Fractals 40(1), 111–129 (2009) 2. : Evolutionary Design of Chaos Control in 1D. , Chen, G. ) Evolutionary Algorithms and Chaotic Systems. SCI, vol. 267, pp. 165–190. Springer, Heidelberg (2010) 3. : Utilization of SOMA and differential evolution for robust stabilization of chaotic Logistic equation. Computers & Mathematics with Applications 60(4), 1026–1037 (2010) 4.
Presently, evolutionary algorithms are known as a powerful set of tools for almost any difficult and complex optimization problem. The interest about the interconnection between evolutionary techniques and control of chaotic systems is spread daily. The first steps were done in  - , where the control law was based on the Pyragas method, which is Extended delay feedback control (ETDAS) . These papers were concerned with tuning several parameters inside the control technique for chaotic system.
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