We describe and apply an iterative, t ime-domain deconvolution approach to receiver-function estimation and illustrate the reliability and advantages of the technique using syntheticand observation-based examples. The iterative technique is commonly used in earthquake t ime-function studies and offers several advantages in receiver-function analysis such as intuitively stripping the largest rec...

This paper shows how bandgap EEL spectra are commonly processed either by deconvolution or subtraction methods in an attempt to remove effects arising from the finite width and long tail of the zero loss peak. This paper will compare the two main methods, and show that the deconvolution method is significantly more reliable and free of user-interpretation or artefacts. We first consider how the...

The iterative blind deconvolution algorithm proposed by Ayers and Dainty [Opt. Lett. 13,547 (1988)] and improved on by Davey et al. [Opt. Commun. 69,353 (1989)] is applied to the problem of phase retrieval, which is a special case of the blind deconvolution problem. A close relationship between this algorithm and the error-reduction version of the iterative Fourier-transform phase-retrieval alg...

Most of the techniques for image restoration are based on some known degradation models. But in many situations it is difficult to accurately measure the degradation factors or noise type that is the real motivation behind the use of blind deconvolution technique for image restoration. Here the observed degraded image is restored without having any prior knowledge about the noise type. Most of ...

In this paper, we propose an approach to the multichannel blind deconvolution problem, based on the mutual information criterion and more generally on an appropriate system of estimating equations. Formulas for the quasiNewton algorithm and the asymptotic covariance matrix of the estimator are provided. More interesting results have been obtained in the pure deconvolution case. By a clever para...

`Bussgang ' deconvolution techniques for blind digital channels equalization rely on a Bayesian estimator of the source sequence deened on the basis of channel/equalizer cascade model which involves the deenition of deconvolution noise. In this paper we consider four`Bussgang' blind deconvolution algorithms for uniformly-distributed source signals and investigate their numerical performances as...

In this paper we apply a recursive deconvolution method to Active Noise Cancellation (ANC) in a linear system: the observation of the output of a linear system of relative degree one, red at discrete time instants, is fed to a deconvolution algorithm which identify the disturbance (with the delay of one step). This information is used in order to reduce the effect of the disturbance itself. Dec...

In this paper, we use a general mathematical and experimental methodology to analyze image deconvolution. The main procedure is to use an example image convolving it with a know Gaussian point spread function and then develop algorithms to recover the image. Observe the deconvolution process by adding Gaussian and Poisson noise at different signal to noise ratios. In addition, we will describe ...

‘Bussgang’ deconvolution techniques for blind digital channels equalization rely on a Bayesian estimator of the source sequence de1ned on the basis of channel=equalizer cascade model which involves the de1nition of deconvolution noise. In this paper we consider four ‘Bussgang’ blind deconvolution algorithms for uniformly distributed source signals and investigate their numerical performances as...

We propose a new two-stage blind separation and deconvolution (BSD) algorithm for a convolutive mixture of speech, in which a new Single-Input Multiple-Output (SIMO)-modelbased ICA (SIMO-ICA) and blind multichannel inverse filtering are combined. SIMO-ICA can separate the mixed signals, not into monaural source signals but into SIMO-model-based signals from independent sources as they are at th...