Active Noise Control Systems: Algorithms and DSP Implementations (Wiley Series in Telecommunications and Signal Processi
Active noise control (ANC) is rapidly becoming the most effective way to reduce noises that can otherwise be very difficult and expensive to control. ANC is achieved by introducing a canceling "anti-noise" wave through an appropriate array of secondary sources. When applied accurately, ANC can provide effective solutions to noise-related problems in a broad range of areas, including manufacturing and industrial operations as well as consumer products. Consequently, ANC research and development has become an important focus of both industrial applications and engineering research.
Active Noise Control Systems: Algorithms and DSP Implementations introduces the basic concepts of ANC with an emphasis on digital signal processing (DSP) hardware and adaptive signal processing algorithms, both of which have come into prominence within the last decade. The authors emphasize the practical aspects of ANC systems by combining the principles of adaptive signal processing with both experimental results and practical implementation. Applications are cited in many fields and encompass all types of noise media, including air-acoustic, hydroacoustic, vibrations, and others. The specific implementation stressed is based on the TMS320 family of signal processors from Texas Instruments, which are the most widely used worldwide.
Coverage of theory includes concise derivations and analyses of commonly used adaptive structures and algorithms for active noise control applications, which are enhanced by the inclusion of a floppy disk featuring C and assembly programs for implementing many ANC systems. Mathematical representations are employed and the source code included on the disk is in a form that is easily accessible to anyone using the book.
For practicing engineers, researchers, and advanced students in signal processing, Active Noise Control Systems: Algorithms and DSP Implementations will serve as a comprehensive, state-of-the-art text/reference on this important and rapidly developing field.
The recent development of digital signal processing (DSP) hardware and adaptive signal processing algorithms has resulted in a dynamic new way of achieving active noise control (ANC). To meet the need for a definitive text on both the basic theory and practical applications of these new ANC techniques, Sen M. Kuo and Dennis R. Morgan have written an invaluable, highly accessible book for researchers, engineers, and advanced students in signal processing.
A state-of-the-art presentation of ANC from innovators in the field
Thorough coverage of the theoretical principles behind ANC techniques with rational and consistent notation
Numerous illustrations for easy interpretation of complex algorithms
Unique emphasis on the practical applications of ANC systems from the viewpoint of signal processing and DSP implementation within the framework of ANC systems
Accompanying software that can be used to implement many ANC systems discussed in the text
Why Read This Book
You should read this book if you need a practical, algorithm-to-hardware guide to active noise control: it connects ANC theory to real DSP implementations and worked adaptive-algorithm examples. It shows how to model secondary paths, implement filtered-x LMS and frequency-domain ANC, and run systems on real DSP platforms.
Who Will Benefit
Engineers and graduate students building or researching ANC systems — particularly those implementing adaptive control on DSP hardware for audio, industrial noise, or vibration reduction.
Level: Advanced — Prerequisites: Undergraduate-level DSP (z-transforms, FIR/IIR filters, FFT), basics of adaptive filters (LMS), linear systems, and familiarity with MATLAB; C or embedded DSP programming experience is highly recommended.
Key Takeaways
- Implement filtered-x LMS and other adaptive ANC algorithms in simulation and on DSP hardware.
- Model and estimate the secondary-path and incorporate its dynamics into stable adaptive control.
- Design and deploy single-channel and multichannel ANC architectures for practical acoustic problems.
- Apply frequency-domain ANC methods to reduce computational load and improve performance for long filters.
- Address stability, convergence, and robustness issues in real-time ANC systems.
- Map algorithmic designs onto DSP platforms (typical fixed-point considerations, block processing, and real-time constraints).
Topics Covered
- Introduction and motivation for active noise control
- Acoustical and signal models for ANC
- Review of adaptive filtering (LMS, NLMS) and control prerequisites
- Filtered-x LMS algorithm and variations
- Secondary-path modeling and identification
- Multichannel ANC architectures and decentralized control
- Frequency-domain ANC and block algorithms
- Stability, convergence, and robustness considerations
- Implementation issues on DSP hardware (fixed-point, delay, buffering)
- Case studies, simulations, and experimental results
- Practical design examples and performance evaluation
- Appendices: math tools, implementation tips, and references
Languages, Platforms & Tools
How It Compares
More implementation-oriented than S. J. Elliott's Active Noise Control texts — Kuo's book emphasizes DSP hardware, filtered-x variants, and practical multichannel implementations; for adaptive-filter theory more generally, compare to Haykin's "Adaptive Filter Theory".
