Cong Wang – författare

Deterministic Learning Theory for Identification, Recognition, and Control presents a unified conceptual framework for knowledge acquisition, representation, and knowledge utilization in uncertain dynamic environments. It provides systematic design approaches for identification, recognition, and control of linear uncertain systems. Unlike many books currently available that focus on statistical principles, this book stresses learning through closed-loop neural control, effective representation and recognition of temporal patterns in a deterministic way.

A Deterministic View of Learning in Dynamic Environments

The authors begin with an introduction to the concepts of deterministic learning theory, followed by a discussion of the persistent excitation property of RBF networks. They describe the elements of deterministic learning, and address dynamical pattern recognition and pattern-based control processes. The results are applicable to areas such as detection and isolation of oscillation faults, ECG/EEG pattern recognition, robot learning and control, and security analysis and control of power systems.

A New Model of Information Processing

This book elucidates a learning theory which is developed using concepts and tools from the discipline of systems and control. Fundamental knowledge about system dynamics is obtained from dynamical processes, and is then utilized to achieve rapid recognition of dynamical patterns and pattern-based closed-loop control via the so-called internal and dynamical matching of system dynamics. This actually represents a new model of information processing, i.e. a model of dynamical parallel distributed processing (DPDP).

Deterministic Learning Theory for Identification, Recognition, and Control presents a unified conceptual framework for knowledge acquisition, representation, and knowledge utilization in uncertain dynamic environments. It provides systematic design approaches for identification, recognition, and control of linear uncertain systems. Unlike many books currently available that focus on statistical principles, this book stresses learning through closed-loop neural control, effective representation and recognition of temporal patterns in a deterministic way.

A Deterministic View of Learning in Dynamic Environments

The authors begin with an introduction to the concepts of deterministic learning theory, followed by a discussion of the persistent excitation property of RBF networks. They describe the elements of deterministic learning, and address dynamical pattern recognition and pattern-based control processes. The results are applicable to areas such as detection and isolation of oscillation faults, ECG/EEG pattern recognition, robot learning and control, and security analysis and control of power systems.

A New Model of Information Processing

This book elucidates a learning theory which is developed using concepts and tools from the discipline of systems and control. Fundamental knowledge about system dynamics is obtained from dynamical processes, and is then utilized to achieve rapid recognition of dynamical patterns and pattern-based closed-loop control via the so-called internal and dynamical matching of system dynamics. This actually represents a new model of information processing, i.e. a model of dynamical parallel distributed processing (DPDP).

This collection addresses the need for sustainable technologies with reduced energy consumption and pollutants and the development and application of alternative sustainable energy to maintain a green environment and energy supply. Contributions focus on energy-efficient technologies including innovative ore beneficiation, smelting technologies, and recycling and waste heat recovery, as well as emerging novel energy technologies. Papers also cover various technological aspects of sustainable energy ecosystems, processes that improve energy efficiency, reduce thermal emissions, and reduce carbon dioxide and other greenhouse emissions.

Energy Technologies and Carbon Dioxide Management

Solar Cell Silicon

Advanced Materials for Energy Conversion and Storage

This collection addresses the pressing needs for sustainable technologies with reduced energy consumption and environmental pollutions and the development and application of alternative sustainable energy to maintain a green environment and efficient and long-lasting energy supply. Contributors represent both industry and academia and focus on new and efficient energy technologies including innovative ore beneficiation, smelting technologies, and recycling and waste heat recovery, as well as emerging novel energy solutions. The volume also covers a broad range of mature and new technological aspects of sustainable energy ecosystems, processes that improve energy efficiency, reduce thermal emissions, and reduce carbon dioxide and other greenhouse emissions. Authors also explore the valorization of materials and their embodied energy including byproducts or coproducts from ferrous and nonferrous industries, batteries, electronics, and other complex secondary materials. 

This book constitutes the proceedings of the satellite workshops held around the 18th International Conference on Applied Cryptography and Network Security, ACNS 2020, in Rome, Italy, in October 2020.

The 31 papers presented in this volume were carefully reviewed and selected from 65 submissions. They stem from the following workshops:

AIBlock 2020:Second International Workshop on Application Intelligence and Blockchain Security

AIHWS 2020:First International Workshop on Artificial Intelligence in Hardware Security

AIoTS 2020:Second International Workshop on Artificial Intelligence and Industrial Internet-of-Things Security

Cloud S&P 2020:Second International Workshop on Cloud Security and Privacy

SCI 2020:First International Workshop on Secure Cryptographic Implementation

SecMT 2020:First International Workshop on Security in Mobile Technologies

SiMLA 2020: Second International Workshop on Security in Machine Learning and its Applications

The 19 revised full papers were carefully reviewed and selected from 49 submissions. The papers are organized thematically in tracks on Network Reliability and Security an Emerging Applications

The 26 papers presented in this volume were carefully reviewed and selected from 49 submissions. They stem from the following workshops:

AIBlock 2021: Third International Workshop on Application Intelligence and Blockchain Security

AIHWS 2021: Second International Workshop on Artificial Intelligence in Hardware Security

AIoTS 2021: Third International Workshop on Artificial Intelligence and Industrial IoT Security

CIMSS 2021: First International Workshop on Critical Infrastructure and Manufacturing System Security

Cloud S&P 2021: Third International Workshop on Cloud Security and Privacy

SCI 2021: Second International Workshop on Secure Cryptographic Implementation

SecMT 2021: Second International Workshop on Security in Mobile Technologies

This book constitutes the proceedings of the satellite workshops held around the 20th International Conference on Applied Cryptography and Network Security, ACNS 2022, held in Rome, Italy, in June 2022. Due to the Corona pandemic the workshop was held as a virtual event. 

The 31 papers presented in this volume were carefully reviewed and selected from 52 submissions. They stem from the following workshops:

– AIHWS: 3rd ACNS Workshop on Artificial Intelligence in Hardware Security

– AIoTS: 4th ACNS Workshop on Artificial Intelligence and Industrial IoT Security

– CIMSS: 2nd ACNS Workshop on Critical Infrastructure and Manufacturing System Security

– Cloud S&P: 4th ACNS Workshop on Cloud Security and Privacy

– SecMT: 3rd ACNS Workshop on Security in Mobile Technologies

– SiMLA: 4th ACNS Workshop on Security in Machine Learning and its Applications

The 34 full papers and 13 poster papers presented in this volume were carefully reviewed and selected from 76 submissions. They stem from the following workshops: