Ralph D. Hippenstiel
Using simplified notation and a practical approach, Detection Theory: Applications and Digital Signal Processing introduces the principles of detection theory, the necessary mathematics, and basic signal processing methods along with some recently developed statistical techniques. Throughout the book, the author keeps the needs of practicing engineers firmly in mind. His presentation and choice of topics allows students to quickly become familiar with the detection and signal processing fields and move on to more advanced study and practice. The author also presents many applications and wide-ranging examples that demonstrate how to apply the concepts to real-world problems.
Introduction. Review of Systems, Signals. Hypothesis Testing. Non-Parametric and Sequential Detection. Detection of Signals in White Gaussian Noise. Detection of Known Signals in Colored Gaussian Noise: Continuous Time Case. Detection of Known Signals in Colored Gaussian Noise: Matrix Based. Detection of Unknown Signals: Discrete Time Case. Wavelets. Polyspectra Time Frequency Representations and Cyclostationary Spectral Density. Estimation. Spectral Estimation. Appendices.
Whether working in wireless communication technology or radar/sonar systems, researchers and engineers must understand the fundamentals of signal detection. While offering a clear, self-contained treatment of the theory behind signal detection, the author incorporates many applications and wide-ranging examples that demonstrate how to apply the concepts to real-world problems. Accessible to senior level undergraduates and suitable as both a text and a reference, this book incorporates treatments of modern concepts, methods, and technologies, including digital signal processing, wavelets, fast Fourier transform processing, and cyclostationary processing.
Whether working in wireless communication technology or radar/sonar systems, researchers and engineers must understand the fundamentals of signal detection. This book includes treatments of modern concepts, methods, and technologies, including digital signal processing, wavelets, fast Fourier transform processing, and cyclostationary processing.
Über den Autor
Ralph D. Hippenstiel
Inhaltsverzeichnis
Introduction. Review of Systems, Signals. Hypothesis Testing. Non-Parametric and Sequential Detection. Detection of Signals in White Gaussian Noise. Detection of Known Signals in Colored Gaussian Noise: Continuous Time Case. Detection of Known Signals in Colored Gaussian Noise: Matrix Based. Detection of Unknown Signals: Discrete Time Case. Wavelets. Polyspectra Time Frequency Representations and Cyclostationary Spectral Density. Estimation. Spectral Estimation. Appendices.
Klappentext
Continuous Signals and Systems with MATLAB is the first undergraduate text fully focused on continuous systems. It presents all of the material needed to master the subject and its related MATLAB problem-solving techniques. The authors cover all of the traditional topics and include chapters on system design, state-space techniques, linearizing nonlinear systems, and the design and analysis of analog filters. They also discuss the five representations of continuous systems and explain how to go from one representation to another.
