As demand for applications working in extended frequency ranges increases, classical Digital signal processing (DSP) techniques, not protected against aliasing, are becoming less effective. Digital alias-free signal processing (DASP) is a technique for overcoming the problems of aliasing at extended frequency ranges. Based on non-uniform or randomised sampling techniques and the development of novel algorithms, it creates the capacity to suppress potential aliasing crucial for high frequency applications and to reduce the complexity of designs.
This book provides practical and comprehensive coverage of the theory and techniques behind alias-free digital signal processing.
Analyses issues of sampling, randomised and pseudo-randomised quantisation and direct and indirectly randomised sampling.
Examines periodic and hybrid sampling, including information on processing algorithms and potential limitations imposed by signal dynamics.
Sets out leading methods and techniques for complexity reduced designs, in particular designs of large aperture sensor arrays, massive data acquisition and compression from a number of signal sources and complexity-reduced processing of non-uniform data.
Presents examples of engineering applications using these techniques including spectrum analysis, waveform reconstruction and the estimation of various parameters, emphasising the importance of the technique for developing new technologies.
Links DASP and traditional technologies by mapping them into embedded systems with standard inputs and outputs.
Digital Alias-free Signal Processing is ideal for practising engineers and researchers working on the development of digital signal processing applications at extended frequencies. It is also a valuable reference for electrical and computer engineering graduates taking courses in signal processing or digital signal processing.
Table of Contents
- Cover Page
- Title Page
- Frequently Used Symbols and Abbreviations
- 1: Introduction: Signal Digitizing and Digital Processing
Part 1: Digitizing
- 2: Randomization as a Tool
- 3: Periodic Versus Randomized Sampling
- 4: Randomized Quantization
- 5: Pseudo-randomized Quantizing
- 6: Direct Randomization of Sampling
- 7: Threshold-crossing Sampling
- 8: Derivatives of Periodic Sampling
- 9: Fuzzy Aliasing
- 10: Hybrid Sampling
Part 2: Processing
- 11: Data Acquisition
- 12: Quantizing-specific Signal Parameter Estimation
- 13: Estimation of Correlation Functions
- 14: Signal Transforms
- 15: DFT of Nonuniformly Sampled Signals
- 16: Complexity-reduced DFT
- 17: Spatial Data Acquisition and Processing
- 18: Adapting Signal Processing to Sampling Nonuniformities
19: Estimation of Object Parameters
- 19.1 Measuring the Frequency Response of Objects
- 19.2 Test Signal Synthesis from a Sparsely Periodically Sampled Basis Function
- 19.3 Test Signal Synthesis from a Nonuniformly Sampled Basis Function
- 19.4 Synthesis of Narrowband and Wideband Signals
- 19.5 Measuring Small Delays and Switching Times
- 19.6 Bioimpedance Signal Demodulation in Real-time
20: Encapsulating DASP Technology
- 20.1 Linking Digital Alias-free Signal Processing with Traditional Methods
- 20.2 Algorithm Options in the Development of Firmware
- 20.3 Dedicated Services of the Embedded DASP Systems
- 20.4 Dedicated Services Related to Processing of Digital Inputs
- 20.5 Reducing the Quantity of Sensors in Large-aperture Arrays
- Title: Digital Alias-free Signal Processing
- Release date: May 2007
- Publisher(s): Wiley
- ISBN: 9780470027387