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Faster data transmission speed and longer distances are more susceptible to errors. CRC (Cyclic Redundancy Checksum) is an efficient and simple cryptic algorithm has been in use among the software community since very long time to detect malicious changes in transmitted data. Recently hardware engineers are also interested in using it in their forward error detection scheme with low resource consumption overhead for their ultra high-speed data communication. To tap the full potential of CRC algorithm in hardware level, it must be implemented in a hardware friendly manner with proper user constraints. This paper presents a very high throughput low latency VLSI design architecture of CRC-32 with reconfigurable parameters. The high throughput is achieved by using expandable data bus line. While, low latency is made possible by parallelizing the logic implementation. The way this problem is approached is elegantly explained using detailed diagrams and mathematics, such that the readers find it easy to adapt the architecture to any CRC polynomial type / size. The uniqueness of our design lies in its ability to operate on the same clock cycle in which the code word is presented, with results produced in immediately next clock cycle. The effects of variations in design parameters of CRC VLSI design on performance characteristics is studied. Also, we have further extended the scope of utility of this component by modeling test scenarios where our CRC logic core is encapsulated to suit different interface standards and how its efficiency changes with chosen interface.
Preface. 1. Introduction. I: Converters in Equilibrium. 2. Principles of Steady State Converter Analysis. 3. Steady-State Equivalent Circuit Modeling, Losses, and Efficiency. 4. Switch Realization. 5. The Discontinuous Conduction Mode. 6. Converter Circuits. II: Converter Dynamics and Control. 7. AC Equivalent Circuit Modeling. 8. Converter Transfer Functions. 9. Controller Design. 10. Input Filter Design. 11. AC and DC Equivalent Circuit Modeling of the Discontinuous Conduction Mode. 12. Current Programmed Control. III: Magnetics. 13. Basic Magnetics Theory. 14. Inductor Design. 15. Transformer Design. IV: Modern Rectifiers and Power System Harmonics. 16. Power and Harmonics in Nonsinusoidal Systems. 17. Line-Commutated Rectifiers. 18. Pulse-Width Modulated Rectifiers. V: Resonant Converters. 19. Resonant Conversion. 20. Soft Switching. Appendices: A. RMS Values of Commonly-Observed Converter Waveforms. B. Simulation of Converters. C. Middlebrook's Extra Element Theorem. D. Magnetics Design Tables. Index.
For the bigger harmonic, lower power factor and poorer dynamic performance of wind power grid PWM rectifier control system, a new control method is put forward. With the space vector pulse modulation, it uses the sliding-mode variable structure control as the voltage loop and current feed-forward decoupled control algorithm as the current-loop. PWM rectifier experiment system is constructed based on TMS320F2812, the experiment results validate the feasibility of the control scheme.
Much has been written about the problems of programming DSPs in a high-level language (HLL) like C. In general, most users are not satisfied with the efficiency of the compilers available for DSPs. Yet, with DSP systems becoming larger and larger, there is increasing need for DSPs to be programmed in an HLL. Rather than focusing on C language efficiency alone, the authors looked at the DSP architectures and the C language itself. The results of efforts in this regard are discussed. The authors report on the DSP/C compiler and its implementation for the ADSP-21020. DSP/C is an HLL intended for DSP application and the ADSP-21020 is an IEEE single precision floating point and 32-bit fixed point DSP designed for HLL application.
Fuzzy neurons and fuzzy neural networks (FNN) are constructs of computational intelligence that come with significant learning abilities and inherent transparency (interpretability). Consequently, they exhibit high potential to provide strong mechanisms for building intelligent systems that must operate in rapidly changing environments. However, to fully exploit the potential of FNN structures, efficient parallel-processing implementations are highly desired. In this study, our objective is to investigate this avenue and identify various critical hardware design issues as we propose a versatile neurofuzzy platform with a topology strongly influenced by theories of fuzzy modelling. With a novel hybrid-learning scheme involving structural and parametric optimization, we demonstrate how fuzzy neural networks are well suited in forming the adaptive logic-processing core of this platform, supporting intelligent information processing. The core emulates aspects of human thought, dealing with information at a granular level and using logic-oriented approximate reasoning to solve a problem. It is able to learn and approximate real-world concepts, building a knowledge base that may be interpreted and modified by the user. Drawing upon this knowledge, a high-speed parallel implementation has potential for performing inference of many simultaneous concepts in real-time, realizing cognition as it perceives the current state of its environment.
Practically all modern control systems are based upon microprocessors and complex microcontrollers that yield high performance and functionality. This volume focuses on the design of computer-controlled systems, featuring computational tools that can be applied directly and are explained with simple paper-and-pencil calculations. The use of computational tools is balanced by a strong emphasis on control system principles and ideas. Extensive pedagogical aids include worked examples, MATLAB macros, and a solutions manual (see inside for details).
The initial chapter presents a broad outline of computer-controlled systems, followed by a computer-oriented view based on the behavior of the system at sampling instants. An introduction to the design of control systems leads to a process-related view and coverage of methods of translating analog designs to digital control. Concluding chapters explore implementation issues and advanced design methods.
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