Magnetic resonance imaging (MRI) is extensively exploited for more accurate pathological changes as well as diagnosis. Conversely, MRI suffers from various shortcomings such as ambient noise from the environment, acquisition noise from the equipment, the presence of background tissue, breathing motion, body fat, etc. Consequently, noise reduction is critical as diverse types of the generated no...

An increasingly popular approach to the acquisition of intraoperative data is the novel Time-of-Flight (ToF) camera technique, which provides surface information with high update rates. This information can be used for intra-operative registration with pre-operative data through surface matching techniques. However, ToF data is subject to different systematic errors and noise, which must be eli...

Autonomous determination of the latitude place movable and immovable objects is used as an independent task, well task initial value for operation both platform platform-free navigation systems. To solve these problems, it necessary to have inertial measurement unit (IMU) with at least three gyroscopes accelerometers. When using IMU, executed by MEMS technology, output signals micromechanical g...

Tracking problem in spherical coordinates with range rate (Doppler) measurements, which would have errors correlated to the range measurement errors, is investigated in this paper. The converted Doppler measurements, constructed by the product of the Doppler measurements and range measurements, are used to replace the original Doppler measurements. A de-noising method based on an unbiased Kalma...

This paper shows a relationship between two diierent approximation techniques: the Support Vector Machines (SVM), proposed by V. Vapnik (1995), and a sparse approximation scheme that resembles the Basis Pursuit De-Noising algorithm (Chen, 1995; Chen, Donoho and Saunders, 1995). SVM is a technique which can be derived from the Structural Risk Minimization Principle (Vapnik, 1982) and can be used...

Electrocardiogram (ECG) signal plays an important role in the diagnosis of cardiovascular disease. However, ECG signal is very faint and always affected by a variety of noise in the process of collecting. How to eliminate the noise effectively is an important issue and has been widely studied for many years. In this paper, we propose a new ECG de-noising method based on translation invariant (T...

Since time immemorial, noise has been a constant source of disturbance to the various entities known to mankind. Noise models of different kinds have been developed to study noise in more detailed fashion over the years. Image processing, particularly, has extensively implemented several algorithms to reduce noise in photographs and pictorial documents to alleviate the effect of noise. Images w...

This paper shows a relationship between two different approximation techniques: the Support Vector Machines (SVM), proposed by V. Vapnik (1995), and a sparse approximation scheme that resembles the Basis Pursuit De-Noising algorithm (Chen, 1995; Chen, Donoho and Saunders, 1995). SVM is a technique which can be derived from the Structural Risk Minimization Principle (Vapnik, 1982) and can be use...

Donoho and Johnstone (1992a) proposed a method for reconstructing an unknown function f on [0; 1] from noisy data di = f(ti) + zi, i = 0; : : : ; n 1, ti = i=n, zi iid N(0; 1). The reconstruction f̂ n is de ned in the wavelet domain by translating all the empirical wavelet coe cients of d towards 0 by an amount p 2 log(n) = p n. We prove two results about that estimator. [Smooth]: With high prob...