The field of cellular neural networks (CNNs) is of growing importance in non­ linear circuits and systems and it is maturing to the point of becoming a new area of study in general nonlinear theory. CNNs emerged through two semi­ nal papers co-authored by Professor Leon O. Chua back in 1988. Since then, the attention that CNNs have attracted in the scientific community has been vast. For instance, there are international workshops dedicated to CNNs and their applications, special issues published in both the International Journal of Circuit Theory and in the IEEE Transactions on Circuits and Systems, and there are also Associate Editors appointed in the latter journal especially for the CNN field. All of this bears witness the importance that CNNs are gaining within the scientific community. Without doubt this book is a primer in the field. Its extensive coverage provides the reader with a very comprehensive view of aspects involved in the theory and applications of cellular neural networks. The authors have done an excellent job merging basic CNN theory, synchronization, spatio­ temporal phenomena and hardware implementation into eight exquisitely written chapters. Each chapter is thoroughly illustrated with examples and case studies. The result is a book that is not only excellent as a professional reference but also very appealing as a textbook. My view is that students as well professional engineers will find this volume extremely useful.

This book commemorates Eric Goles’s achievements in science and engineering. Eric Goles is one of the world leaders in the field of automata and complexity. His groundbreaking discoveries are in the theory and analysis of complex systems, particularly in the field of discrete systems dynamics such as neural networks, automata networks, majority networks, bootstrap percolation models, cellular automata, computational complexity theory, discrete mathematics, and theoretical computer science. Topics include cellular automata, complex networks, models of computation, expansive systems, sandpile automata, Penrose tilings, Boolean automata, models of infection, Fibonacci trees, dominos, reversible automata, and fungal automata.

The operation of understanding is the fundamental methodical procedure of hermeneutics and is usually seen as contradiction to scientific explanation by the usage of mathematical models. Yet understanding is the basic way in which humans organize their everyday practice, namely by understanding other people and social situations. In this book the authors demonstrate how an integration of hermeneutical understanding and scientific explanation can be done via the construction of suited geometrical models with neural networks of processes of understanding. In this sense the authors develop some kind of mathematical hermeneutics. Connecting links for the integration of the two methodical poles are the developments of particular models of Artificial Intelligence (AI), which are able to perform certain tasks of understanding.

The four-volume set LNCS 11256, 11257, 11258, and 11259 constitutes the refereed proceedings of the First Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2018, held in Guangzhou, China, in November 2018.

This book commemorates Eric Goles’s achievements in science and engineering. Eric Goles is one of the world leaders in the field of automata and complexity. His groundbreaking discoveries are in the theory and analysis of complex systems, particularly in the field of discrete systems dynamics such as neural networks, automata networks, majority networks, bootstrap percolation models, cellular automata, computational complexity theory, discrete mathematics, and theoretical computer science. Topics include cellular automata, complex networks, models of computation, expansive systems, sandpile automata, Penrose tilings, Boolean automata, models of infection, Fibonacci trees, dominos, reversible automata, and fungal automata.

This book presents the proceedings of the 14th International Conference on Applications of Fuzzy Systems, Soft Computing, and Artificial Intelligence Tools, ICAFS-2020, held in Budva, Montenegro, on August 27–28, 2020. It includes contributions from diverse areas of fuzzy systems, soft computing, AI tools such as uncertain computation, decision making under imperfect information, deep learning and others.

​This book is focused on the use of deep learning (DL) and artificial intelligence (AI) as tools to advance the fields of malware detection and analysis. The individual chapters of the book deal with a wide variety of state-of-the-art AI and DL techniques, which are applied to a number of challenging malware-related problems. DL and AI based approaches to malware detection and analysis are largely data driven and hence minimal expert domain knowledge of malware is needed.