In the last decade new artificial intelligence methods for the modelling and control of complex systems, namely neural networks, fuzzy logic and probabilistic reasoning have drawn the interest of researchers and engineers. Recently, the advantages achievable by using combinations of these methods, which have independent origin and evolution, have been pointed out, generating a new paradigm which is now termed "soft-computing". This new methodology subsumes the capabilities of neural networks for modelling non-linear systems and for solving classification problems, the power of fuzzy-logic to represent approximate or heuristic reasoning and the large capabilities of evolutionary computation for problem optimisation. The book presents a clear understanding of a new type of computation system, the cellular neural network (CNN), which has been successfully applied to the solution of many heavy computation problems, mainly in the fields of image processing and complex partial differential equations. CNNs'' computation-based systems represent new opportunities for improving the soft-computation toolbox. The application of soft computing to complex systems and in particular to chaotic systems with the generation of chaotic dynamics by using CNN is also described. These aspects are of particular interest owing to their growing interest for research and application purposes.Specific topics covered in the text include:- fuzzy logic, control and neural networks;- artificial neural networks and their application in the modelling and control of dynamical systems;- evolutionary optimisation algorithms;- complex dynamics and cellular neural networks;- applications in urban traffic noise monitoring, robot control and rapid thermal process systems.

In the last decade new artificial intelligence methods for the modelling and control of complex systems, namely neural networks, fuzzy logic and probabilistic reasoning have drawn the interest of researchers and engineers. Recently, the advantages achievable by using combinations of these methods, which have independent origin and evolution, have been pointed out, generating a new paradigm which is now termed "soft-computing". This new methodology subsumes the capabilities of neural networks for modelling non-linear systems and for solving classification problems, the power of fuzzy-logic to represent approximate or heuristic reasoning and the large capabilities of evolutionary computation for problem optimisation. The book presents a clear understanding of a new type of computation system, the cellular neural network (CNN), which has been successfully applied to the solution of many heavy computation problems, mainly in the fields of image processing and complex partial differential equations. CNNs' computation-based systems represent new opportunities for improving the soft-computation toolbox. The application of soft computing to complex systems and in particular to chaotic systems with the generation of chaotic dynamics by using CNN is also described. These aspects are of particular interest owing to their growing interest for research and application purposes.Specific topics covered in the text include:- fuzzy logic, control and neural networks;- artificial neural networks and their application in the modelling and control of dynamical systems;- evolutionary optimisation algorithms;- complex dynamics and cellular neural networks;- applications in urban traffic noise monitoring, robot control and rapid thermal process systems.

This book focuses on two specific areas related to fractional order systems – the realization of physical devices characterized by non-integer order impedance, usually called fractional-order elements (FOEs); and the characterization of vegetable tissues via electrical impedance spectroscopy (EIS) – and provides readers with new tools for designing new types of integrated circuits. The majority of the book addresses FOEs.The interest in these topics is related to the need to produce “analogue” electronic devices characterized by non-integer order impedance, and to the characterization of natural phenomena, which are systems with memory or aftereffects and for which the fractional-order calculus tool is the ideal choice for analysis.FOEs represent the building blocks for designing and realizing analogue integrated electronic circuits, which the authors believe hold the potential for a wealth of mass-market applications. The freedom to choose either an integer- or non-integer-order analogue integrator/derivator is a new one for electronic circuit designers. The book shows how specific non-integer-order impedance elements can be created using materials with specific structural properties.EIS measures the electrical impedance of a specimen across a given range of frequencies, producing a spectrum that represents the variation of the impedance versus frequency – a technique that has the advantage of avoiding aggressive examinations.Biological tissues are complex systems characterized by dynamic processes that occur at different lengths and time scales; this book proposes a model for vegetable tissues that describes the behavior of such materials by considering the interactions among various relaxing phenomena and memory effects.

This book focuses on two specific areas related to fractional order systems – the realization of physical devices characterized by non-integer order impedance, usually called fractional-order elements (FOEs); and the characterization of vegetable tissues via electrical impedance spectroscopy (EIS) – and provides readers with new tools for designing new types of integrated circuits. The majority of the book addresses FOEs.

The interest in these topics is related to the need to produce “analogue” electronic devices characterized by non-integer order impedance, and to the characterization of natural phenomena, which are systems with memory or aftereffects and for which the fractional-order calculus tool is the ideal choice for analysis.

FOEs represent the building blocks for designing and realizing analogue integrated electronic circuits, which the authors believe hold the potential for a wealth of mass-market applications. The freedom to choose either an integer- or non-integer-order analogue integrator/derivator is a new one for electronic circuit designers. The book shows how specific non-integer-order impedance elements can be created using materials with specific structural properties.

EIS measures the electrical impedance of a specimen across a given range of frequencies, producing a spectrum that represents the variation of the impedance versus frequency – a technique that has the advantage of avoiding aggressive examinations.

Biological tissues are complex systems characterized by dynamic processes that occur at different lengths and time scales; this book proposes a model for vegetable tissues that describes the behavior of such materials by considering the interactions among various relaxing phenomena and memory effects.

This book focuses on the research topics investigated during the three-year research project funded by the Italian Ministero dell'Istruzione, dell'Università e della Ricerca (MIUR: Ministry of Education, University and Research) under the FIRB project RBNE01CW3M. With the aim of introducing newer perspectives of the research on complexity, the final results of the project are presented after a general introduction to the subject. The book is intended to provide researchers, PhD students, and people involved in research projects in companies with the basic fundamentals of complex systems and the advanced project results recently obtained.Sample Chapter(s)

In the last decade new artificial intelligence methods for the modelling and control of complex systems, namely neural networks, fuzzy logic and probabilistic reasoning have drawn the interest of researchers and engineers. Recently, the advantages achievable by using combinations of these methods, which have independent origin and evolution, have been pointed out, generating a new paradigm which is now termed "soft-computing". This new methodology subsumes the capabilities of neural networks for modelling non-linear systems and for solving classification problems, the power of fuzzy-logic to represent approximate or heuristic reasoning and the large capabilities of evolutionary computation for problem optimisation. The book presents a clear understanding of a new type of computation system, the cellular neural network (CNN), which has been successfully applied to the solution of many heavy computation problems, mainly in the fields of image processing and complex partial differential equations. CNNs'' computation-based systems represent new opportunities for improving the soft-computation toolbox. The application of soft computing to complex systems and in particular to chaotic systems with the generation of chaotic dynamics by using CNN is also described. These aspects are of particular interest owing to their growing interest for research and application purposes.Specific topics covered in the text include:- fuzzy logic, control and neural networks;- artificial neural networks and their application in the modelling and control of dynamical systems;- evolutionary optimisation algorithms;- complex dynamics and cellular neural networks;- applications in urban traffic noise monitoring, robot control and rapid thermal process systems.

In the last decade new artificial intelligence methods for the modelling and control of complex systems, namely neural networks, fuzzy logic and probabilistic reasoning have drawn the interest of researchers and engineers. Recently, the advantages achievable by using combinations of these methods, which have independent origin and evolution, have been pointed out, generating a new paradigm which is now termed "soft-computing". This new methodology subsumes the capabilities of neural networks for modelling non-linear systems and for solving classification problems, the power of fuzzy-logic to represent approximate or heuristic reasoning and the large capabilities of evolutionary computation for problem optimisation. The book presents a clear understanding of a new type of computation system, the cellular neural network (CNN), which has been successfully applied to the solution of many heavy computation problems, mainly in the fields of image processing and complex partial differential equations. CNNs' computation-based systems represent new opportunities for improving the soft-computation toolbox. The application of soft computing to complex systems and in particular to chaotic systems with the generation of chaotic dynamics by using CNN is also described. These aspects are of particular interest owing to their growing interest for research and application purposes.Specific topics covered in the text include:- fuzzy logic, control and neural networks;- artificial neural networks and their application in the modelling and control of dynamical systems;- evolutionary optimisation algorithms;- complex dynamics and cellular neural networks;- applications in urban traffic noise monitoring, robot control and rapid thermal process systems.

This book focuses on two specific areas related to fractional order systems – the realization of physical devices characterized by non-integer order impedance, usually called fractional-order elements (FOEs); and the characterization of vegetable tissues via electrical impedance spectroscopy (EIS) – and provides readers with new tools for designing new types of integrated circuits. The majority of the book addresses FOEs.The interest in these topics is related to the need to produce “analogue” electronic devices characterized by non-integer order impedance, and to the characterization of natural phenomena, which are systems with memory or aftereffects and for which the fractional-order calculus tool is the ideal choice for analysis.FOEs represent the building blocks for designing and realizing analogue integrated electronic circuits, which the authors believe hold the potential for a wealth of mass-market applications. The freedom to choose either an integer- or non-integer-order analogue integrator/derivator is a new one for electronic circuit designers. The book shows how specific non-integer-order impedance elements can be created using materials with specific structural properties.EIS measures the electrical impedance of a specimen across a given range of frequencies, producing a spectrum that represents the variation of the impedance versus frequency – a technique that has the advantage of avoiding aggressive examinations.Biological tissues are complex systems characterized by dynamic processes that occur at different lengths and time scales; this book proposes a model for vegetable tissues that describes the behavior of such materials by considering the interactions among various relaxing phenomena and memory effects.

This book focuses on two specific areas related to fractional order systems – the realization of physical devices characterized by non-integer order impedance, usually called fractional-order elements (FOEs); and the characterization of vegetable tissues via electrical impedance spectroscopy (EIS) – and provides readers with new tools for designing new types of integrated circuits. The majority of the book addresses FOEs.

The interest in these topics is related to the need to produce “analogue” electronic devices characterized by non-integer order impedance, and to the characterization of natural phenomena, which are systems with memory or aftereffects and for which the fractional-order calculus tool is the ideal choice for analysis.

FOEs represent the building blocks for designing and realizing analogue integrated electronic circuits, which the authors believe hold the potential for a wealth of mass-market applications. The freedom to choose either an integer- or non-integer-order analogue integrator/derivator is a new one for electronic circuit designers. The book shows how specific non-integer-order impedance elements can be created using materials with specific structural properties.

EIS measures the electrical impedance of a specimen across a given range of frequencies, producing a spectrum that represents the variation of the impedance versus frequency – a technique that has the advantage of avoiding aggressive examinations.

Biological tissues are complex systems characterized by dynamic processes that occur at different lengths and time scales; this book proposes a model for vegetable tissues that describes the behavior of such materials by considering the interactions among various relaxing phenomena and memory effects.

This book focuses on the research topics investigated during the three-year research project funded by the Italian Ministero dell'Istruzione, dell'Università e della Ricerca (MIUR: Ministry of Education, University and Research) under the FIRB project RBNE01CW3M. With the aim of introducing newer perspectives of the research on complexity, the final results of the project are presented after a general introduction to the subject. The book is intended to provide researchers, PhD students, and people involved in research projects in companies with the basic fundamentals of complex systems and the advanced project results recently obtained.Sample Chapter(s)