Real-time systems design and analysis [[electronic resource] /] / Phillip A. Laplante

• Record Nr.: UNINA9910143643703321
• Autore: Laplante Phillip A
• Pubbl/distr/stampa: Hoboken, N.J., : Wiley, 2004
• ISBN: 1-280-36809-8; 9786610368099; 0-470-34265-X; 0-471-64828-0; 0-471-64829-9
• Edizione: [3rd ed.]
• Descrizione fisica: 1 online resource (529 p.)
• Disciplina: 001.6; 004.33
• Soggetti: Real-time data processing; System design
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references (p. 475-485) and index.
• Nota di contenuto: REAL-TIME SYSTEMS DESIGN AND ANALYSIS; CONTENTS; Preface to the Third Edition; 1 Basic Real-Time Concepts; 1.1 Terminology; 1.1.1 Systems Concepts; 1.1.2 Real-Time Definitions; 1.1.3 Events and Determinism; 1.1.4 CPU Utilization; 1.2 Real-Time System Design Issues; 1.3 Example Real-Time Systems; 1.4 Common Misconceptions; 1.5 Brief History; 1.5.1 Theoretical Advances; 1.5.2 Early Systems; 1.5.3 Hardware Developments; 1.5.4 Early Software; 1.5.5 Commercial Operating System Support; 1.6 Exercises; 2 Hardware Considerations; 2.1 Basic Architecture; 2.2 Hardware Interfacing; 2.2.1 Latching; 2.2.2 Edge versus Level Triggered2.2.3 Tristate Logic; 2.2.4 Wait States; 2.2.5 Systems Interfaces and Buses; 2.3 Central Processing Unit; 2.3.1 Fetch and Execute Cycle; 2.3.2 Microcontrollers; 2.3.3 Instruction Forms; 2.3.4 Core Instructions; 2.3.5 Addressing Modes; 2.3.6 RISC versus CISC; 2.4 Memory; 2.4.1 Memory Access; 2.4.2 Memory Technologies; 2.4.3 Memory Hierarchy; 2.4.4 Memory Organization; 2.5 Input/Output; 2.5.1 Programmed Input/Output; 2.5.2 Direct Memory Access; 2.5.3 Memory-Mapped Input/Output; 2.5.4 Interrupts; 2.6 ; Enhancing Performance; 2.6.1 Locality of Reference; 2.6.2 Cache; 2.6.3 Pipelining2.6.4 Coprocessors; 2.7 Other Special Devices; 2.7.1 Applications-Specific Integrated Circuits; 2.7.2 Programmable Array Logic/Programmable Logic Array; 2.7.3 Field-Programmable Gate Arrays; 2.7.4 Transducers; 2.7.5 Analog/Digital Converters; 2.7.6 Digital/Analog Converters; 2.8 Non-von-Neumann Architectures; 2.8.1 Parallel Systems; 2.8.2 Flynn's Taxonomy for Parallelism; 2.9 Exercises; 3 Real-Time Operating Systems; 3.1 Real-Time Kernels; 3.1.1 Pseudokernels; 3.1.2 Interrupt-Driven Systems; 3.1.3 Preemptive-Priority Systems; 3.1.4 Hybrid Systems; 3.1.5 The Task-Control Block Model3.2 Theoretical Foundations of Real-Time Operating Systems; 3.2.1 Process Scheduling; 3.2.2 Round-Robin Scheduling; 3.2.3 Cyclic Executives; 3.2.4 Fixed-Priority Scheduling-Rate-Monotonic Approach; 3.2.5 Dynamic-Priority Scheduling: Earliest-Deadline-First Approach; 3.3 Intertask Communication and Synchronization; 3.3.1 Buffering Data; 3.3.2 Time-Relative Buffering; 3.3.3 Ring Buffers; 3.3.4 Mailboxes; 3.3.5 Queues; 3.3.6 Critical Regions; 3.3.7 Semaphores; 3.3.8 Other Synchronization Mechanisms; 3.3.9 Deadlock; 3.3.10 Priority Inversion; 3.4 Memory Management3.4.1 Process Stack Management; 3.4.2 Run-Time Ring Buffer; 3.4.3 Maximum Stack Size; 3.4.4 Multiple-Stack Arrangements; 3.4.5 Memory Management in the Task-Control-Block Model; 3.4.6 Swapping; 3.4.7 Overlays; 3.4.8 Block or Page Management; 3.4.9 Replacement Algorithms; 3.4.10 Memory Locking; 3.4.11 Working Sets; 3.4.12 Real-Time Garbage Collection; 3.4.13 Contiguous File Systems; 3.4.14 Building versus Buying Real-Time Operating Systems; 3.4.15 Selecting Real-Time Kernels; 3.5 Case Study: POSIX; 3.5.1 Threads; 3.5.2 POSIX Mutexes and Condition Variables; 3.5.3 POSIX Semaphores
• Sommario/riassunto: The leading guide to real-time systems design-revised and updatedThis third edition of Phillip Laplante's bestselling, practical guide to building real-time systems maintains its predecessors' unique holistic, systems-based approach devised to help engineers write problem-solving software. Dr. Laplante incorporates a survey of related technologies and their histories, complete with time-saving practical tips, hands-on instructions, C code, and insights into decreasing ramp-up times.Real-Time Systems Design and Analysis, Third Edition is essential for students and practicing sof

Neural Information Processing . Part V : 29th International Conference, ICONIP 2022, Virtual Event, November 22-26, 2022, Proceedings / / Mohammad Tanveer [and four others], editors

• Record Nr.: UNISA996547957003316
• Pubbl/distr/stampa: Singapore : , : Springer, , [2023]; ©2023
• ISBN: 981-9916-42-9
• Edizione: [First edition.]
• Descrizione fisica: 1 online resource (XXXV, 609 p. 196 illus., 173 illus. in color.)
• Collana: Communications in Computer and Information Science Series ; ; Volume 1792
• Disciplina: 006.3
• Soggetti: Neural computers; Neural networks (Computer science)
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Theory and Algorithms II -- GCD-PKAug: A Gradient Consistency Discriminator-based Augmentation Method for Pharmacokinetics Time Courses -- ISP-FESAN: Improving Significant Wave Height Prediction with Feature Engineering and Self-Attention Network -- Binary Orthogonal Non-negative Matrix Factorization -- Shifted Chunk Encoder for Transformer Based Streaming End-to-End ASR -- Interpretable Decision Tree Ensemble Learning with Abstract Argumentation for Binary Classification -- Adaptive Graph Recurrent Network for Multivariate Time Series Imputation -- Adaptive Rounding Compensation for Post-Training Quantization -- More Efficient And Locally Enhanced Transformer -- ASLEEP: A Shallow neural modEl for knowlEdge graph comPletion -- A speech enhancement method combining two-branch communication and spectral subtraction -- A fast and robust Photometric redshift forecasting method using Lipschitz adaptive learning rate -- Generating Textual Description using Modified Beam Search -- Disentangling Exploration and Exploitation in Deep Reinforcement Learning Using Contingency Awareness -- Multi-Grained Fusion Graph Neural Networks for Sequential Recommendation -- Optimal Design of Cable-Driven Parallel Robots by Particle Schemes -- UPFP-growth++: An Efficient Algorithm ; to Find Periodic-Frequent Patterns in Uncertain Temporal Databases -- Active Learning with Weak Supervision for Gaussian Processes -- HPC based Scalable Logarithmic Kernelized Fuzzy Clustering Algorithms for Handling Big Data -- Cognitive Neurosciences -- RTS:A Regional Time Series Framework for Brain Disease Classification -- Deep Domain Adaptation for EEG-based Cross-subject Cognitive Workload Recognition -- Graph Convolutional Neural Network Based on Channel Graph Fusion for EEG Emotion Recognition -- Detecting Major Depressive Disorder by Graph Neural Network Exploiting Resting-state Functional MRI -- An Improved Stimulus Reconstruction Method for EEG-based Short-time Auditory Attention Detection -- Functional Connectivity of the Brain while Solving Scientific Problems with Uncertainty as Revealed by Phase Synchronization based on Hilbert Transform -- Optimizing pcsCPD with Alternating Rank-R and Rank-1 Least Squares: Application to Complex-Valued Multi-Subject fMRI Data -- Decoding Brain Signals with Meta-Learning -- Human Centered Computing -- Research on Answer Generation for Chinese Gaokao Reading Comprehension -- A Novel Graph Transformer Based Approach Toward Multi-hop Question Answering -- Logit Distillation via Student Diversity -- Causal connectivity transition from action observation to mentalizing network for understanding other’s action intention -- ND-NER: A Named Entity Recognition Dataset for OSINT towards the National Defense Domain -- Extractive Question Answering using Transformer-based LM -- Temporal dynamics of value integration in perceptual decisions: An EEG study -- Measuring Decision Confidence Levels from EEG Using a Spectral-Spatial-Temporal Adaptive Graph Convolutional Neural Network -- BPMCF: Behavior Preference Mapping Collaborative Filtering for Multi-Behavior Recommendation -- Neural Distinguishers on TinyJAMBU-128 and GIFT-64 -- Towards Hardware-friendly and Robust Facial Landmark Detection Method -- Few-shot Class-incremental Learning for EEG-based Emotion Recognition -- Motor Imagery BCI-based Online Control Soft Glove Rehabilitation System with Vibrotactile Stimulation -- Multi-level visual feature enhancement method for visual question answering -- Learning from Hindsight Demonstrations -- Hindsight Balanced Reward Shaping -- Emotion Recognition with Facial Attention and Objective Activation Functions -- M3S-CNN: Resting-state EEG based Multimodal and Multiscale Feature Extraction for Student Status Prediction in Class -- Towards Human Keypoint Detection in Infrared Images -- Multi-human intelligence in Instance-Based Learning -- How the Presence of Cognitive Biases in Phishing Emails Affects Human Decision-making? -- A simple memory module on reading comprehension -- Predicting Parkinson’s Disease Severity Using Patient-Reported Outcomes and Genetic Information -- Towards the Development of a Machine Learning-based Action Recognition Model to Support Positive Behavioural Outcomes in Students with Autism -- Safety Issues Investigation in Deep Learning based Chatbots Answers to Medical Advice Requests.
• Sommario/riassunto: The four-volume set CCIS 1791, 1792, 1793 and 1794 constitutes the refereed proceedings of the 29th International Conference on Neural Information Processing, ICONIP 2022, held as a virtual event, November 22–26, 2022. The 213 papers presented in the proceedings set were carefully reviewed and selected from 810 submissions. They were organized in topical sections as follows: Theory and Algorithms; Cognitive Neurosciences; Human Centered Computing; and Applications. The ICONIP conference aims to provide a leading international forum for researchers, scientists, and industry professionals who are working in neuroscience, neural networks, deep ; learning, and related fields to share their new ideas, progress, and achievements.