Algorithms for Verifying Deep Neural Networks

Algorithms for Verifying Deep Neural Networks
Author: Changliu Liu
Publisher:
Total Pages:
Release: 2021-02-11
Genre:
ISBN: 9781680837865

Neural networks have been widely used in many applications, such as image classification and understanding, language processing, and control of autonomous systems. These networks work by mapping inputs to outputs through a sequence of layers. At each layer, the input to that layer undergoes an affine transformation followed by a simple nonlinear transformation before being passed to the next layer. Neural networks are being used for increasingly important tasks, and in some cases, incorrect outputs can lead to costly consequences, hence validation of correctness at each layer is vital. The sheer size of the networks makes this not feasible using traditional methods. In this monograph, the authors survey a class of methods that are capable of formally verifying properties of deep neural networks. In doing so, they introduce a unified mathematical framework for verifying neural networks, classify existing methods under this framework, provide pedagogical implementations of existing methods, and compare those methods on a set of benchmark problems. Algorithms for Verifying Deep Neural Networks serves as a tutorial for students and professionals interested in this emerging field as well as a benchmark to facilitate the design of new verification algorithms.

Methods and Procedures for the Verification and Validation of Artificial Neural Networks

Methods and Procedures for the Verification and Validation of Artificial Neural Networks
Author: Brian J. Taylor
Publisher: Springer Science & Business Media
Total Pages: 280
Release: 2006-03-20
Genre: Computers
ISBN: 0387294856

Neural networks are members of a class of software that have the potential to enable intelligent computational systems capable of simulating characteristics of biological thinking and learning. Currently no standards exist to verify and validate neural network-based systems. NASA Independent Verification and Validation Facility has contracted the Institute for Scientific Research, Inc. to perform research on this topic and develop a comprehensive guide to performing V&V on adaptive systems, with emphasis on neural networks used in safety-critical or mission-critical applications. Methods and Procedures for the Verification and Validation of Artificial Neural Networks is the culmination of the first steps in that research. This volume introduces some of the more promising methods and techniques used for the verification and validation (V&V) of neural networks and adaptive systems. A comprehensive guide to performing V&V on neural network systems, aligned with the IEEE Standard for Software Verification and Validation, will follow this book.

Automated Technology for Verification and Analysis

Automated Technology for Verification and Analysis
Author: Dang Van Hung
Publisher: Springer Nature
Total Pages: 575
Release: 2020-10-12
Genre: Computers
ISBN: 3030591522

This book constitutes the refereed proceedings of the 18th International Symposium on Automated Technology for Verification and Analysis, ATVA 2020, held in Hanoi, Vietnam, in October 2020. The 27 regular papers presented together with 5 tool papers and 2 invited papers were carefully reviewed and selected from 75 submissions. The symposium is dedicated to promoting research in theoretical and practical aspects of automated analysis, verification and synthesis by providing an international venue for the researchers to present new results. The papers focus on neural networks and machine learning; automata; logics; techniques for verification, analysis and testing; model checking and decision procedures; synthesis; and randomization and probabilistic systems.

Automated Technology for Verification and Analysis

Automated Technology for Verification and Analysis
Author: Ahmed Bouajjani
Publisher: Springer Nature
Total Pages: 442
Release: 2022-10-22
Genre: Computers
ISBN: 3031199928

This book constitutes the refereed proceedings of the 20th International Symposium on Automated Technology for Verification and Analysis, ATVA 2022, held in Beiging, China in October 2022. The symposium is dedicated to promoting research in theoretical and practical aspects of automated analysis, verification and synthesis by providing an international venue for the researchers to present new results. The 21 regular papers presented together with 5 tool papers and 1 invited paper were carefully reviewed and selected from 81 submissions. The papers are divided into the following topical sub-headings: reinforcement learning; program analysis and verification; smt and verification; automata and applications; active learning; probabilistic and stochastic systems; synthesis and repair; and verification of neural networks.

Neural Network Control Of Robot Manipulators And Non-Linear Systems

Neural Network Control Of Robot Manipulators And Non-Linear Systems
Author: F W Lewis
Publisher: CRC Press
Total Pages: 470
Release: 1998-11-30
Genre: Technology & Engineering
ISBN: 9780748405961

There has been great interest in "universal controllers" that mimic the functions of human processes to learn about the systems they are controlling on-line so that performance improves automatically. Neural network controllers are derived for robot manipulators in a variety of applications including position control, force control, link flexibility stabilization and the management of high-frequency joint and motor dynamics. The first chapter provides a background on neural networks and the second on dynamical systems and control. Chapter three introduces the robot control problem and standard techniques such as torque, adaptive and robust control. Subsequent chapters give design techniques and Stability Proofs For NN Controllers For Robot Arms, Practical Robotic systems with high frequency vibratory modes, force control and a general class of non-linear systems. The last chapters are devoted to discrete- time NN controllers. Throughout the text, worked examples are provided.

PROCEEDINGS OF THE 24TH CONFERENCE ON FORMAL METHODS IN COMPUTER-AIDED DESIGN – FMCAD 2024

PROCEEDINGS OF THE 24TH CONFERENCE ON FORMAL METHODS IN COMPUTER-AIDED DESIGN – FMCAD 2024
Author: Nina Narodytska
Publisher: TU Wien Academic Press
Total Pages: 316
Release: 2024-10-01
Genre: Computers
ISBN: 3854480652

Die Proceedings zur Konferenz „Formal Methods in Computer-Aided Design 2024“ geben aktuelle Einblicke in ein spannendes Forschungsfeld. Zum fünften Mal erscheinen die Beiträge der Konferenzreihe „Formal Methods in Computer-Aided Design“ (FMCAD) als Konferenzband bei TU Wien Academic Press. Der aktuelle Band der seit 2006 jährlich veranstalteten Konferenzreihe präsentiert in 35 Beiträgen neueste wissenschaftliche Erkenntnisse aus dem Bereich des computergestützten Entwerfens. Die Beiträge behandeln formale Aspekte des computergestützten Systemdesigns einschließlich Verifikation, Spezifikation, Synthese und Test. Die FMCAD-Konferenz findet im Oktober 2024 in Prag, Tschechische Republik, statt. Sie gilt als führendes Forum im Bereich des computer-aided design und bietet seit ihrer Gründung Forschenden sowohl aus dem akademischen als auch dem industriellen Umfeld die Möglichkeit, sich auszutauschen und zu vernetzen.

Nonlinear System Identification

Nonlinear System Identification
Author: Oliver Nelles
Publisher: Springer Science & Business Media
Total Pages: 785
Release: 2013-03-09
Genre: Technology & Engineering
ISBN: 3662043238

Written from an engineering point of view, this book covers the most common and important approaches for the identification of nonlinear static and dynamic systems. The book also provides the reader with the necessary background on optimization techniques, making it fully self-contained. The new edition includes exercises.

Safe, Autonomous and Intelligent Vehicles

Safe, Autonomous and Intelligent Vehicles
Author: Huafeng Yu
Publisher: Springer
Total Pages: 215
Release: 2018-11-14
Genre: Technology & Engineering
ISBN: 3319973010

This book covers the start-of-the-art research and development for the emerging area of autonomous and intelligent systems. In particular, the authors emphasize design and validation methodologies to address the grand challenges related to safety. This book offers a holistic view of a broad range of technical aspects (including perception, localization and navigation, motion control, etc.) and application domains (including automobile, aerospace, etc.), presents major challenges and discusses possible solutions.

Methods and Procedures for the Verification and Validation of Artificial Neural Networks

Methods and Procedures for the Verification and Validation of Artificial Neural Networks
Author: Brian J. Taylor
Publisher: Springer Science & Business Media
Total Pages: 300
Release: 2006
Genre: Computers
ISBN: 9780387282886

Neural networks are members of a class of software that have the potential to enable intelligent computational systems capable of simulating characteristics of biological thinking and learning. This volume introduces some of the methods and techniques used for the verification and validation of neural networks and adaptive systems.