L. R. Rabiner and B. Gold. Theory and Application of Digital Signal Processing. Prentice Hall, 1975.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....3: Comparison of asynchronous FX[REF ] and F 0[PDA] contours on male speech 5. CONCLUSION The probabilistic error correction is quite different from most other techniques that have been used to correct pitch estimate errors [11, 14] In contrast to both linear and nonlinear filtering techniques [10], the preservation and use of markers ensures that the final pitch estimate for a frame is in fact drawn from one of the AMDF candidates for the frame s pitch. No logic based decisions are used, as required in [11] The probabilistic error correction involves significantly less computation than ....

L.R. Rabiner and B. Gold. Theory and application of digital signal processing. Prentice Hall, Englewood Cliffs, NJ, 1975.

....in the passband and stopband: The transition bandwidth is critical to the relation of the filter length to the distance from an ideal one zero response. A useful formula derived experimentally by Kaiser [7] suggests an appropriate filter length. There are similar formulas in Rabiner and Gold [12] and Vaidyanathan [14] Kaiser s is the simplest and most characteristic (1) For this value of , the Remez algorithm yields the frequency response closest to the ideal one zero function on the union of passband and stopband . The code outputs the coefficients of this Manuscript received ....

....on but not on (3) Since the are not identical, does exist. When must be at the unique critical point . Remark 2: For optimal polynomial approximation, real analysis yields the famous alternation theorem (the equiripple property and exchange algorithm; see Cheney [2] and Rabiner and Gold [12]) The deeper asymptotic problems require complex analysis and potential theory. We recommend the classical monographs by Walsh [15] and Henrici [6] Appendix D contains a short survey on the connection between optimal polynomial approximation and potential theory. C. Leading Order for It is ....

[Article contains additional citation context not shown here]

L. R. Rabiner and B. Gold, Theory and Application of Digital Signal Processing. Englewood Cliffs, NJ: Prentice-Hall, 1975.

....function of a FIR filter of length N, which can be represented as H(z) N h(n z n . 1) 4n=0 Depending on the values of N (odd or even ) and type of symmetry of the filter impulse response h(n) symmetric or antisymmetric) there are four possible types of linear phase FIR filters [9]. The amplitude response of these four types of filters can be expressed as A(rO) Znb (nF(m,n) 2 where T(o,n) is an appropriate trigonometric function and coefficients b(n) is related to impulse response h(n) of the filter whereas M is a function of the filter length N. Table 1 lists the ....

....with symmetrical impulse response ( case 1 and 2) can be used for the design of even order differentiaters. However, while case 1 is suitable for designing full band or nonfull band DD s, case 2 is useful only for designing nonfull band DD s due to the inherent zero folding frequency constraint [9]. Similarly, for an odd order DD (k is odd) the fact that Hi(c 0) is purely imaginary function, mandates the design of a FIR filter with an antisymmetrical impulse response (case 3 and 4) For odd order DD s case 3 is only suitable for designing the nonfull band DD due to the inherent zero ....

L.R. Rabiner and B. Gold, Theory and Applications of Digital Signal Processing, Prentice-Hall, Englewood Cliff's, NJ 1975. 6

....response from the output of the storage device to the output of the filter. Obviously, in the majority of the practical cases these state variable values are not known. However, their possible range can be estimated. It is well known from the literature of digital signal processing (see, e.g. [RG75]) that different structures have quite different internal dynamic ranges. As an example, consider the first order direct structure in Fig. 3.1(a) Z 1 Z 1 Z 1 u(n) y(n) a 1 b 0 b 1 Z 1 Z 1 Z 1 u(n) y(n) r 0 1 w 0 d (a) x(n) x(n 1) x(n 1) x(n) b) Fig. 3.1. a) ....

....sixth order resonator based structure. 14 As another simple example Table 3. 2 summarizes the behavior of four different alternatives for the realization of the very same first order difference equation (transfer function) The first three are the most widely used versions of the direct structure [RG75], while the fourth one is again the resonator based structure [PMP96] The coefficients provide low pass behavior, and again the step response is investigated. The outputs y(n) 1 as n . It is assumed, that at n 0 the outputs take the value of 0.5. At n 0 1 with the old parameter set each ....

[Article contains additional citation context not shown here]

Rabiner, L.R., B. Gold, Theory and Application of Digital Signal Processing. Englewood Cliffs, NJ: Prentice-Hall, 1975.

....kind of feedback control system. Particularly interesting examples are the feedback control systems that are employed in robots and satellites (devices that comprise a sensor and an actuator) and a class of finite impulse response filters that are extensively used in digital signal processing [RG75] Our hope is that self testing techniques for linear recurrences can be applied to test hardware for such systems. This promises new, exciting, and realistic applications of self testers in general. Results. Our main result in this paper is a complete set of simple self testers self correctors ....

L. Rabiner and B. Gold. Theory and Application of Digital Signal Processing. PrenticeHall, 1975.

....j 0 j = S a k jm . Proof of Theorem 2. Given k and m, form the periodic sequence with terms a k p = j = S a k jm . 7) The series in (7) converges absolutely since j = S a j . Next construct the discrete Fourier transform of a k p , see p. 51 of Rabiner and Gold [12], to obtain a k p = m 1 j = 0 S m 1 a j p e i2pkj m = m 1 j = 0 S m 1 l = S a j lm e i2p jk m = m 1 j = S a j e i2p jk m = m 1 f m 2pk . Finally, from the inversion formula for discrete Fourier transforms, a k p = ....

L. R. Rabiner and B. Gold, Theory and Application of Digital Signal Processing (Prentice-Hall, Englewood Cliffs, New Jersey, 1975).

....A D, D A converters. 1. INTRODUCTION Although the classical solutions in digital signal processing offer very well established methods for the frequencydomain signal representation like the discrete Fourier Transformation (DFT) and its fast algorithm the fast Fourier Transformation (FFT) [1,2] we have to face serious limits due to the contradictory requirements of magnitude and frequency resolution. To reduce these problems recently the application of multi sine perturbation signals came into focus [9] Another disadvantageous aspect is that the widely used FFT techniques are ....

....[9] Another disadvantageous aspect is that the widely used FFT techniques are operated block orientedly, i.e. process given blocks of data, so do not directly support real time signal processing which also has become an important claim in this field. Using the classical recursive DFT methods [1] the realtime processing can be solved with a higher computational burden relative to the FFT. Later the classical version based on the Lagrange structure has been replaced by an observer structure [3,4] however, computational complexity remained the same. Recently a fast implementation of the ....

L.R. Rabiner, B. Gold, Theory and Application of Digital Signal Processing, Prentice-Hall, Englewood Cliffs, NJ, 1975.

....of the discrete Fourier transform) of a k : 0 k 2mn 1 in (4. 10) so that F( j t n) can be efficiently calculated for all j, 0 j 2mn 1, for large mn (when n 2mn and n is chosen to be a power of 2) by using a Fast Fourier Transform (FFT) see pages 51 and 357 368 of Rabiner and Gold [102], Cooley and Tukey [25] Cooley, Lewis and Welch [22] 23] 24] and Dubner and Abate [40] This reduces the computational burden from n 2 to n log 2 n. In addition to being computationally efficient when n is large, an FFT may be convenient because an FFT program is readily available. FFTs ....

....The essential idea is to approximate the given function by a periodic function that can be represented by its Fourier series. This explains the name Fourier series method. In the signal processing and time series literature, this is called aliasing; e.g. pp. 26 28 of Rabiner and Gold [102]. Probability Densities Starting with a function f (t) which we will regard as a probability density, the idea is to construct the periodic function f p (t) k = S f (t 2pk h) 5.1) of period 2p h, which usually can be made suitably close to f (t) by choosing h small. We then ....

[Article contains additional citation context not shown here]

L. R. Rabiner and B. Gold, Theory and Application of Digital Signal Processing. (Prentice-Hall, Englewood Cliffs, New Jersey, 1975).

....examples to show how this new approach can be used in a variety of situations. 2. The Algorithm There are 4 different types of linear phase filters. For both even and odd symmetry of the impulse response, we obtain linear phase with either even or odd number of coefficients. In Rabiner and Gold [17] it is shown that the frequency response for each of the 4 types of linear phase filters has the form H( Omega Gamma = e j 2 L e Gammaj Omega Gamma N Gamma1 2 ) A( Omega Gamma where the real valued amplitude function A( Omega Gamma is a weighted sum of trigonometric functions, where N ....

L.R. Rabiner and B. Gold, Theory and Application of Digital Signal Processing, Prentice-Hall, Englewood Cliffs, New Jersey, 1975; see pp. 75--84.

....width rest of signal i i i i = 5.1) 5.3.2 The filters. The main objective with applying a filter to a signal is to reduce the noise and unwanted signals without disturbing the wanted ones. There are several ways of doing this, which leads to different types of filters [18]. Filtering is used to reduce the amplitude of a part of the spectrum of the whole signal. If the spectral information of the noise and the real signal are at different frequencies, we can suppress that way the noise part. After retransformation to the time domain we obtain the filtered ....

L. R. Rabiner & B. Gold ; Theory and Application of Digital Signal processing, Prentice Hall, London, 1975.

....Fig. 3. Polyphase DFT synthesizer for N = 8 where x(n) denotes the nth input sample, Xm the mth DFT component. The standard form of the recursive evaluation is simply a sliding window technique for calculating the Fourier coefficients and or components with respect to the last N input samples [5], 6] Recently a new technique has been developed for the implementation of the recursive DFT based on the concepts of polyphase filtering and the fast Fourier transformation (FFT) 2] The novelty of this approach is the decomposition of a larger size single input multiple output (SIMO) DFT ....

....of the individual filters within the bank, however, are not selective enough if measurement noise is also present in the signal. The noise immunity can be improved by further averaging. III. Recursive DFT Filter Bank with Fading Memory As it is well known from the literature (see e.g. [5]) the averaging effect in (1) can have an interesting frequencydomain interpretation. One of the typical characterizations is the z domain transfer function of the averager 1 N 1 Gamma z GammaN 1 Gamma z Gamma1 : 2) This transfer function is present in every sliding DFT channel that ....

[Article contains additional citation context not shown here]

L.R. Rabiner, B. Gold, Theory and Application of Digital Signal Processing, Prentice-Hall, Englewood Cliffs, NJ, 1975.

No context found.

L. R. Rabiner and B. Gold. Theory and Application of Digital Signal Processing. Prentice Hall, 1975.

No context found.

L. R. Rabiner and B. Gold, Theory and Application of Digital Signal Processing. Englewood Cliffs, NJ: Prentice-Hall, 1975, p. 47.

No context found.

L. Rabiner and B. Gold. Theory and Application of Digital Signal Processing. Prentice Hall, Englewood Cliffs, NJ, 1975. 44

No context found.

L.R. Rabiner and B. Gold. Theory and Application of Digital Signal Processing. Prentice-Hall Signal Processing Series. Prentice-Hall, Englewood Cli#s (NJ), USA, 1975.

No context found.

L. R. Rabiner and B. Gold, "Theory and Application of Digital Signal Processing", Prentice-Hall, Englewood Cli#s, New Jersey, 1975.

No context found.

Bernard Gold, Lawrence R. Rabiner, "Theory and Application of Digital Signal Processing", Prentice-Hall, Inc., 1975.

No context found.

Rabiner, L.R., and B. Gold (1975). Theory and Application of Digital Signal Processing, Prentice Hall, Englewood Cliffs.

No context found.

Rabiner, L., B. Gold. "Theory and Applications of Digital Signal Processing." Prentice Hall 1975.

No context found.

L. R. Rabiner and B. Gold, Theory and Application of Digital Signal Processing. Englewood Cliffs, NJ: Prentice-Hall, 1975.

No context found.

Gold, B., Rabiner, L. R. (1975) Theory and Application of Digital Signal Processing, PrenticeHall, Inc. Englewood Cliffs, New Jersey.

No context found.

Rabiner, L. R., and Gold, B., Theory and Application of Digital Signal Processing, Prentice -- Hall, Englewood Cliffs, NJ, 1975. J. C. Taylor Associate Editor

No context found.

L. R. Rabiner and B. Gold, Theory and application of digital signal processing. Englewood Cliffs, NJ: PrenticeHall, 1975.

No context found.

L. R. Rabiner and B. Gold, Theory and Application of Digital Signal Processing (Prentice-Hall, 1975).

No context found.

Rabiner, l., and Gold, B., Theory and application of digital signal processing, Englewood Cliffs, NJ: PrenticeHall, 1975.

First 50 documents  Next 50

Online articles have much greater impact   More about CiteSeer.IST   Add search form to your site   Submit documents   Feedback  

CiteSeer.IST - Copyright Penn State and NEC