Convolution is a linear operation, and, consequently, can be formulated as a linear system of equations. If only the output of the system (the convolved signal) is known, then the problem is blind so that given one equation, two unknowns are sought. Here, the blind deconvolution problem is solved using independent component analysis (ICA). To facilitate this, several time lagged versions of the...

A simple iterative algorithm, termed deconvolution-interpolation gridding (DING), is presented to address the problem of reconstructing images from arbitrarily-sampled k-space. The new algorithm solves a sparse system of linear equations that is equivalent to a deconvolution of the k-space with a small window. The deconvolution operation results in increased reconstruction accuracy without grid...

purpose: to evaluate the efficacy, safety, predictability and stability of implantable collamer lens (icl) and toric icl for the treat­ment of high myopia and high myopic astigmatism, one year prospective study. methods: in this prospective nonrandomized clinical trial, 95 eyes of 51 patients that had icl (31 eyes) and toric icl (64 eyes) were participate in eye research center, department of o...

In this paper, we propose a new approach to wavelet-based deconvolution. Roughly speaking, the algorithm comprises Fourierdomain system inversion followed by wavelet-domain noise suppression. Our approach subsumes a number of other wavelet-based deconvolution methods. In contrast to other wavelet-based approaches, however, we employ a regularized inverse filter, which allows the algorithm to op...

Deconvolution refers to the problem of estimating the unknown input to an LTI system when the output signal and system response are known. In practice, the available output signal is also noisy. For some systems, the deconvolution problem is quite straight forward; however, for systems that are non-invertible or nearly non-invertible (e.g. narrow-band or with frequency response nulls), the prob...

In this study, a new method called the pixel basis functional radionuclide imaging (PBFRI) algorithm based on the appended curve deconvolution technique, in order to be able to increase the medical diagnostic capability of a conventional gamma camera, is presented together with the clinical results. In the PBFRI method, retention function of each pixel is obtained from the renograms and cardiac...

were P(t) is lidar observation after deconvolution process, strongly dependent on geometrical and optical characteristics of the sensor, and Pδ(t) is ideal observation when the response funtion of lidar sensor is a Diràc distribution, like ideal laser pulse. From (1), the additive noise term N(t) makes a direct deconvolution impossible. In general, deconvolution process with R(t) show a low-pas...

Spontaneous postsynaptic currents (PSCs) provide key information about the mechanisms of synaptic transmission and the activity modes of neuronal networks. However, detecting spontaneous PSCs in vitro and in vivo has been challenging, because of the small amplitude, the variable kinetics, and the undefined time of generation of these events. Here, we describe a, to our knowledge, new method for...

In the communication field, during transmission, a source signal undergoes a convolutive distortion between its symbols and the channel impulse response. This distortion is referred to as Intersymbol Interference (ISI) and can be reduced significantly by applying a blind adaptive deconvolution process (blind adaptive equalizer) on the distorted received symbols. But, since the entire blind deco...

In this paper, Shalvi and Weinstein's 1-dimensional (1-D) computationally efficient super-exponential (SE) algorithm for blind deconvolution is extended to 2-dimensional (2-D) SE algorithm. Then a noiseinsensitive 2-D blind system identification (BSI) algorithm using the computationally efficient 2-D SE algorithm is proposed for the estimation of 2-D linear shift-invariant (LSI) systems. Moreov...