Abstract: A new method for numerical deconvolution is described, for use in calculating drug input rates. The method is based on the least-squares criterion and approximates the input rate by a polynomial function. Ill-conditioning of the normal equations is avoided by using orthogonal functions. The use of the method is illustrated by means of examples, using simulated data.

Abstract: It is common practice to model a seismic trace as a convolution of the reflectivity function of the earth and an energy waveform referred to as the seismic wavelet. The objective of deconvolution is to extract the reflectivity function from the seismic trace. We will describe four techniques which have been and are being used to accomplish this objective. These techniques are predictive deconvolution, homomorphic filtering, Kalman filtering, and deterministic deconvolution. In addition, we shall outline the physical effects governing the bandwidth of the seismic data such as shooting geometry, recording filters, and absorption.

Abstract: Seismic signals are often modeled as the convolution of a wavelet with the earth reflectivity function. Deconvolution, for the purpose of obtaining the reflectivity function, can be done using state space estimation methods. Such methods are hampered, however, by lack of precise modeling information. The deconvolution problem then becomes an adaptive estimation problem. In this paper the correct model is assumed to be one of a finite set of candidate models, and adaptive deconvolution is accomplished using estimation algorithms developed for this type of model uncertainty.

Abstract: A deconvolution scheme is presented for the calculation of an input function given a system and its response—by converting the integral equation into an initial value problem. This technique is particularly simple and advantageous when dealing with compartmental systems and solving them numerically. The method also permits the imbedding of constraints and the estimation of confidence limits for the deconvoluted function.

Abstract: Distortion caused by the passage of an electrocardiogram (ECG) through a linear, time-invariant system can be removed by deconvolving the impulse response of the distorting system from the observation. By modeling the ECG as a cyclostationary signal, the deconvolution can be done without a priori knowledge of the impulse response of the distorting system.

Abstract: A deconvolution algorithm is presented for calculating the N tap weights of a transversal-filter equaliser. The procedure attempts to control the size of individual, time-domain response errors rather than simply minimise total mean-square error of the response. A least-square error solution for the tap weights is iteratively modified, using only elementary algebraic matrix operations, in an effort to satisfy tolerance constraints on the envelope of the equalised impulse response. The algorithm is suitable for digital computation.

Abstract: Digital deconvolution of instrumentally broadened spectra is characterized by an improvement of resolution and an amplification of noise. By noise simulation we have studied the relation between these properties when the deconvolution interval is bounded by regions with negligible influence of instrumental broadening. These boundary conditions lead to a relevant reduction of noise amplification for rectangular and triangular convolution functions, but have less practical interest for bell-shaped convolution functions.

Abstract: In the deconvolution problem, the presence of noise introduces large errors in the vicinity of the zero-crossings \omega_{i} of the system function. A simple method is presented for reducing

Abstract: It is shown that a number of well known iterative deconvolution algorithms are closely related members of a general class. This point of view leads to new understanding of previous approaches and to a new algorithm that incorporates both a finite interval constraint and a positivity constraint on the output of the deconvolution process. Examples are given to illustrate performance on gamma-ray spectra.

Abstract: A new method for numerical deconvolution is described, for use in calculating drug input rates. The method is based on the least-squares criterion and is applicable when the input function can be assumed to take a prescribed form. In particular, an exponential input function and an input function derived from the cube-root dissolution law are considered. The stability of the method to data noise is shown by means of examples, using simulated data.