Mathematical Methods and Algorithms for Signal Processing tackles the challenge of providing readers and practitioners with the broad tools of mathematics employed in modern signal processing. Building from an assumed background in signals and stochastic processes, the book provides a solid foundati
Mathematical Methods and Algorithms for Signal Processing
โ Scribed by Todd K. Moon, Wynn C. Stirling
- Publisher
- Prentice Hall
- Year
- 1999
- Tongue
- English
- Leaves
- 975
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
Mathematical Methods and Algorithms for Signal Processing tackles the challenge of providing readers and practitioners with the broad tools of mathematics employed in modern signal processing. Building from an assumed background in signals and stochastic processes, the book provides a solid foundation in analysis, linear algebra, optimization, and statistical signal processing. Interesting modern topics not available in many other signal processing books; such as the EM algorithm, blind source operation, projection on convex sets, etc., in addition to many more conventional topics such as spectrum estimation, adaptive filtering, etc. For those interested in signal processing.
๐ SIMILAR VOLUMES
Part 1 Signal analysis: Complex analysis; The delta function; The Fourier series; The Fourier transform; Other integral transforms. Part 2 Computational linear algebra; Matrices and matrix algebra; Direct methods of solution; Iterative methods of solution; Eigen values and Eigen vectors. Part 3 Pro
<p>The series Advances in Industrial Control aims to report and encourage technology transfer in control engineering. The rapid development of control technology impacts all areas of the control discipline. New theory, new controllers, actuators, sensors, new industrial processes, computer methods,
Efficient signal processing algorithms are important for embedded and power-limited applications since, by reducing the number of computations, power consumption can be reduced significantly. Similarly, efficient algorithms are also critical to very large scale applications such as video processing
Efficient signal processing algorithms are important for embedded and power-limited applications since, by reducing the number of computations, power consumption can be reduced significantly. Similarly, efficient algorithms are also critical to very large scale applications such as video processing