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A methodology has been proposed recently to predict error rates of cascade structures of blocks in Probabilistic CMOS (PCMOS). It requires characterization of unique probabilistic blocks to predict the error rates of a multi-block cascade structure. While the technique was shown to work for a probabilistic carry-select adder, the technique needs a new model to work in a Wallace Tree Multiplier (WTM)...
Ventriculomegaly is one of the most sensitive markers for abnormal development of the fetal central nervous system. So assessment of the size of lateral ventricles has become an important part of routine neurological assessment in neonates. We have proposed a method for measuring the width of lateral ventricles in term and preterm neonates from the coronal view of their brain ultrasound images. Based...
A harmonic radar employing the use of harmonic passive RF tags can be successfully used to isolate the human respiration from environmental clutter. This paper describes the successful use of heterodyne receiver architecture with Doppler radar to track the heart-rate of a human being using passive body-worn harmonic tags in presence of a controlled noise generator at distances up to 120 cm. The heterodyne...
In this paper we present a new model for characterization of probabilistic gates. While still not mainstream, probabilistic CMOS has the potential to dramatically reduce energy consumption by trading off with error rates on individual bits, e.g., least significant bits of an adder. Our contribution helps account for the filtering effect seen in noise based PCMOS in a novel way. The characterization...
Correntropy has been recently defined as a localised similarity measure between two random variables, exploiting higher order moments of the data. This paper presents the use of correntropy as a cost function for minimizing the error between the desired signal and the output of an adaptive filter, in order to train the filter weights.We have shown that this cost function has the computational simplicity...
Auto-regulatory transcriptional feedback, where the protein expressed from a gene inhibits its own transcription, is known to reduce stochastic fluctuations in protein numbers. Work has demonstrated the existence of negative feedback loops not only at the transcriptional level but also at the translational level. We investigate the noise suppression abilities of feedback loops at the translational...
The proof of capacity theorem assumed that the symbols are of infinite time duration. Since the infinite time symbols are not meaningful and is not used in the existing technology, in this paper we decided to prove it over finite time interval. The result shows that the new capacity of a band limited channel explicitly depends on the sample rate. This new approach helps us to show that all shift keying...
Image deblurring and denoising are the main steps in early vision problems. A common problem in deblurring is the ringing artifacts created by trying to restore the unknown point spread function (PSF). The random noise present makes this task even harder. Variational blind deconvolution methods add a smoothness term for the PSF as well as for the unknown image. These methods can amplify the outliers...
Living cells are characterized by small populations of key molecular components that have large stochastic noise associated with them. Various gene network motifs exist within cells that help reduce these stochastic fluctuations. A common such motif is an auto-regulatory gene network where the protein expressed from the gene inhibits its own transcription. Here the transcription rate of the gene is...
Using the edge detection techniques we propose a new enhancement scheme for noisy digital images. This uses inhomogeneous anisotropic diffusion scheme via the edge indicator provided by well known edge detection methods. Addition of a fidelity term facilitates the proposed scheme to remove the noise while preserving edges. This method is general in the sense that it can be incorporated into any of...
A new class of variational-PDE based models is proposed for edge preserving image enhancement. Using the equivalence relation between regularization and PDEs we propose a general class of models which restore noisy images with selective enhancement. It contains a controlled inverse diffusion term which sharpens the image. Experiments show the effectiveness of the model with real and MRI images.
Stochastic fluctuations in protein levels are inevitable due to the probabilistic nature of gene expression. These fluctuations are attributed to two factors: intrinsic noise (noise associated with random transcription and translation events) and extrinsic noise (noise associated with fluctuations in the reaction rates due to correspondent fluctuations in cellular enzyme levels). We present results...
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