5 edition of **Digital spectral analysis** found in the catalog.

- 273 Want to read
- 32 Currently reading

Published
**1987** by Prentice-Hall in Englewood Cliffs, N.J .

Written in English

- Spectral theory (Mathematics),
- Signal processing -- Digital techniques.

**Edition Notes**

Includes bibliographies and index.

Statement | S. Lawrence Marple, Jr. |

Series | Prentice-Hall signal processing series |

Classifications | |
---|---|

LC Classifications | QA280 .M38 1987 |

The Physical Object | |

Pagination | xx, 492 p. : |

Number of Pages | 492 |

ID Numbers | |

Open Library | OL2716295M |

ISBN 10 | 0132141493 |

LC Control Number | 86009391 |

To separate two closely spaced frequencies, the sample spacing must be smaller than the distance between the two peaks. Third, the window reduces the resolution in the spectrum by making the peaks wider. Which method should you use? Gerber, H. It is discovered that potential wells of small depth adjacent to the anode appear on the spatial potential profiles at certain moments in time. Since the DFT?

Bibliography PART 4. The second factor limiting resolution is more subtle. Spectral analysis using dated samples To explore the theoretical aspects of this in more detail, imagine an infinitely long discrete sine wave at a frequency of 0.

Estimation of the power spectral density 5. Going through the calculations, this provides about the same noise and resolution as the first method, where the 16, points would be broken into 64 segments of points each. All that can be seen is a noisy waveform that conveys little information to the human eye. A low-pass digital filter is then used to smooth the spectrum, reducing the noise at the expense of the resolution.

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These N points must contain all the nonzero points identified by the window, but may also include any number of the zeros. General mathematical techniques for analyzing non-periodic functions fall into the category of Fourier analysis.

Unfortunately, this also looks like a noisy mess. Figure a shows samples from our imaginary experiment. Part II covers digital signals, demonstrating their key advantages.

Start by taking a very long DFT, say 16, points. In spite of this very close sampling, the Digital spectral analysis book to separate closely spaced peaks would be only slightly better than using a point DFT.

The third part of the book is devoted to random signals, including spectral estimation, parametric modeling, and Tikhonov regularization. Each concept is introduced and explained step by step, and the necessary mathematical formulae are integrated in an accessible and intuitive way.

Order selection criteria 6. Since it cannot be represented by a single sample, it becomes a peak with tails that extend a significant distance away. Non-parametric spectral estimation They alert us when OverDrive services are not working as expected.

Glossary Chapter Also expect to see smaller peaks at multiples of this frequency, hertz, etc.

About this title Digital Spectral Analysis offers a broad perspective of spectral estimation techniques and their Digital spectral analysis book.

Above 70 hertz, the white noise rapidly decreases in amplitude. More than likely, the nearest sample will be slightly off-center, giving a value lower Digital spectral analysis book the true amplitude.

Conclusion 9. Estimation of signal properties is discussed in the context of ergodicity conditions and parameter estimations, including the use of Wiener and Kalman filters.

Model, concept of subspace, definition of high resolution 8. The peak at 13 hertz is called the fundamental frequency, while the peaks at 26 and 39 hertz are referred to as the second and third harmonic respectively. We will come back to this issue shortly. It presents z and Fourier transforms, digital filtering, inverse filters, deconvolution, and parametric modeling for deterministic signals.

Going through the calculations, this provides about the same noise and resolution as the first method, where the 16, points would be broken into 64 segments of points each. The first factor is the length of the DFT. Topics include Prony's method, parametric methods, the minimum variance method, eigenanalysis-based estimators, multichannel methods, and two-dimensional methods.

This brings in the second way we need to modify the time domain signal to allow it to be represented in a computer: select N points from the signal. It has been measured in very diverse systems, such as traffic density on freeways and electronic noise in transistors.

Figure b shows that the spectrum is changed in three ways by using Digital spectral analysis book window. Details on the particle volume monitor statistical sampling noise; Speculations on the physical nature and Introduction 9.

We will discuss the theoretical reasons for this in later chapters; for now, here is a cookbook description of how the technique is used. With this book, digital signal processing leaves the domain of engineering to address the needs Digital spectral analysis book scientists and scholars in traditionally less quantitative disciplines, now facing increasing amounts of data.Particle Filtering and Tracking of Varying Sinusoids David BONACCI Particle filtering Application to spectral analysis Bibliography List of Authors Index (source: Nielsen Book Data) Summary Digital Spectral Analysis provides a single source that offers complete coverage of the spectral analysis domain.

Spectral Audio Signal Processing. The focus of this book is on spectral modeling applied to audio signals. More completely, the principal tasks are spectral. A broad discussion is presented of spectral estimation techniques and their implementation.

The topics addressed include: reviews of linear systems, transform theory, matrix algebra, and random process theory; classical spectral estimation; parametric models of random processes; autoregressive process and spectrum properties; block data algorithms and sequential data algorithms in Cited by: Digital Spectral Analysis offers pdf broad perspective of spectral estimation techniques and their implementation.

Coverage includes spectral estimation of discrete-time or discrete-space sequences derived by sampling continuous-time or continuous-space signals.A DIGITAL SPECTRAL ANALYSIS TECHNIQUE AND ITS APPLICATION TO RADIO ASTRONOMY Sander Weinreb Submitted to the Department of Electrical Engineering, M.I.T., Februaryin partial fulfillment of the requirements for the degree of Doctor of Philosophy.

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