This book explores how neural networks can be designed to analyze sensory data in a way that mimics natural systems. It introduces readers to the cellular neural network (CNN) and formulates it to match the behavior of the Wilson–Cowan model. In turn, two properties that are vital in nature are added to the CNN to help it more accurately deliver mimetic behavior: randomness of connection, and the presence of different dynamics (excitatory and inhibitory) within the same network. It uses an ID matrix to determine the location of excitatory and inhibitory neurons, and to reconfigure the network to optimize its topology. The book demonstrates that reconfiguring a single-layer CNN is an easier and more flexible solution than the procedure required in a multilayer CNN, in which excitatory and inhibitory neurons are separate, and that the key CNN criteria of a spatially invariant template and local coupling are fulfilled. In closing, the application of the authors’ neuron population model as a feature extractor is exemplified using odor and electroencephalogram classification.

The two-volume set LNCS 5601 and LNCS 5602 constitutes the refereed proceedings of the Third International Work-Conference on the Interplay between Natural and Artificial Computation, IWINAC 2009, held in Santiago de Compostela, Spain, in June 2009. The 108 revised papers presented are thematically divided into two volumes. The first volume includes papers relating the most recent collaborations with Professor Mira and contributions mainly related with theoretical, conceptual and methodological aspects linking AI and knowledge engineering with neurophysiology, clinics and cognition. The second volume contains all the contributions connected with biologically inspired methods and techniques for solving AI and knowledge engineering problems in different application domains.

This volume covers the fundamental theory of Cellular Neural Networks as well as their applications in various fields such as science and technology. It contains all 83 papers of the 7th International Workshop on Cellular Neural Networks and their Applications. The workshop follows a biennial series of six workshops consecutively hosted in Budapest (1990), Munich, Rome, Seville, London and Catania (2000).

This volume constitutes the proceedings of the 5th International Conference on Computer Analysis of Images and Patterns (CAIP'93), held in Budapest, Hungary, in September 1993. Formerly, the events in this biennial conference series were thought as a forum where East European researchers and professionals from academia and industry had an opportunity to discuss their results and ideas with Western colleagues active in image processing and pattern recognition. Now, CAIP'93 has a much more international scope, and in the future these conferences will not any longertake place only in East European countries, but roam throughout whole Europe. Besides invited talks by Belikova, Gimel'farb, Haralick and Roska, the volume contains 114 contributions, either presented as lectures or posters and carefully selected by a highly competent international program committee from a total of some 230 submissions; thus the book gives a thorough survey on recent research results and their applications in image processing and pattern recognition. The proceedings is organized in 20 sections, for example on image data structures, image processing, edges and contours, Hough transforms and related methods, shape, motion, 3-D vision, character recognition and document processing, biomedical applications, industrial applications, and neural networks.

The two volumes, LNCS 6686 resp. LNCS 6687, constitute the refereed proceedings of the 4th International Work-Conference on the Interplay between Natural and Artificial Computation, IWINAC 2011, held in La Palma, Canary Islands, Spain, in May/June 2011. The 108 revised full papers presented in LNCS 6686 resp. LNCS 6687 were carefully reviewed and selected from numerous submissions. The first part, LNCS 6686, entitled "Foundations on Natural and Artificial Computation", includes all the contributions mainly related to the methodological, conceptual, formal, and experimental developments in the fields of neurophysiology and cognitive science. The second part, LNCS 6687, entitled "New Challenges on Bioinspired Applications", contains the papers related to bioinspired programming strategies and all the contributions related to the computational solutions to engineering problems in different application domains, specially Health applications, including the CYTED ``Artificial and Natural Computation for Health'' (CANS) research network papers.

This book presents recent applications and approaches as well as challenges in digital forensic science. One of the evolving challenges that is covered in the book is the cloud forensic analysis which applies the digital forensic science over the cloud computing paradigm for conducting either live or static investigations within the cloud environment. The book also covers the theme of multimedia forensics and watermarking in the area of information security. That includes highlights on intelligence techniques designed for detecting significant changes in image and video sequences. Moreover, the theme proposes recent robust and computationally efficient digital watermarking techniques. The last part of the book provides several digital forensics related applications, including areas such as evidence acquisition enhancement, evidence evaluation, cryptography, and finally, live investigation through the importance of reconstructing the botnet attack scenario to show the malicious activities and files as evidences to be presented in a court.