A Class of Stochastic Adaptive Filters

2011 ◽  
pp. 29-48
Author(s):  
Jacob Benesty ◽  
Constantin Paleologu ◽  
Tomas Gänsler ◽  
Silviu Ciochină
Keyword(s):  
Adaptive Filters

Adaptive Filters with Codified Error LMS Algorithm

2006 ◽  
Vol 65 (6) ◽  
pp. 567-579 ◽  
Author(s):  
Jose Velazquez-Lopez ◽  
Juan Carlos Sanchez-Garcia ◽  
Hector Manuel Perez-Meana
Keyword(s):  
Adaptive Filters ◽  
Lms Algorithm

A Variable Step-Size for Sparse Nonlinear Adaptive Filters

2021 ◽  
Author(s):  
Alberto Carini ◽  
Markus V. S. Lima ◽  
Hamed Yazdanpanah ◽  
Simone Orcioni ◽  
Stefania Cecchi
Keyword(s):  
Adaptive Filters ◽  
Variable Step Size ◽  
Step Size ◽  
Variable Step

Realization of Enhanced LMS Filter Using Carry Skip Adder And Quantum Dot Cellular Automation In VLSI For Removing Impulse Noises In Medical Image

2019 ◽  
Vol 14 ◽  
Author(s):  
K.R. Shankarkumar ◽  
Gokul Kumar
Keyword(s):  
Adaptive Filtering ◽  
Adaptive Filters ◽  
Pass Band ◽  
Least Mean Square ◽  
Low Pass ◽  
Parallel Prefix ◽  
Loop Feedback ◽  
Band Pass ◽  
The Difference ◽  
Prefix Adder

: Filtering is an important step in the field of image processing to suppress the required parts or to remove any artifacts present in it. There are different types of filters like low pass, high pass, Band pass, IIR, FIR and adaptive filtering etc.., in these filters adaptive filters is an important filter because it is used to remove the noisy signal and images. Least Mean Square filter is a type of an adaptive filtering which is used to remove the noises present in the medical images. The working of LMS is based on the minimization of the difference between the error images using a closed loop feedback. Therefore presented technique called as Q-CSKA. Here the CSKA performs its operation in stages which is based on the nucleus stage. In the traditional CSKA the nucleus stage is depend on the parallel prefix adder in this work it is replaced by the QCA adder. The QCA adder utilizes the less area compared to PPA and it can be realized in Nanometer range also. For multiplexers, And OR Invert, OR and Invert logic is used to reduce the area and delay. Due to these advantages of the QCA, AOI-OAI logic the proposed method outperformed the LMS implementation in area, power, and accuracy and delay, this based five type image noise of medical pictures related to the best technique is out comes. It helps to medicinal practitioner to resolve the symptoms of patient with ease.

Convex Combination of Spline Adaptive Filters

2019 ◽  
Author(s):  
Michele Scarpiniti ◽  
Danilo Comminiello ◽  
Aurelio Uncini
Keyword(s):  
Adaptive Filters ◽  
Convex Combination

Signal Processing Enhanced Fiber Vibration Sensors

2013 ◽  
Vol 543 ◽  
pp. 302-305
Author(s):  
Daniele Tosi ◽  
Massimo Olivero ◽  
Alberto Vallan ◽  
Guido Perrone
Keyword(s):  
Signal Processing ◽  
Optical Fibers ◽  
Adaptive Filters ◽  
Spectral Estimation ◽  
Cost Effective ◽  
Fiber Sensors ◽  
High Frequencies ◽  
Vibration Sensors ◽  
Signal Processing Algorithms ◽  
Plastic Optical Fibers

The paper analyzes the feasibility of cost-effective fiber sensors for the measurement of small vibrations, from low to medium-high frequencies, in which the complexity of the measurement is moved from expensive optics to cheap electronics without losing too much performance thanks to signal processing algorithms. Two optical approaches are considered: Bragg gratings in standard telecom fibers, which represent the most common type of commercial fiber sensors, and specifically developed sensors made with plastic optical fibers. In both cases, to keep the overall cost low, vibrations are converted into variations of the light intensity, although this makes the received signal more sensitive to noise. Then, adaptive filters and advanced spectral estimation techniques are used to mitigate noise and improve the sensitivity. Preliminary results have demonstrated that the combined effect of these techniques can yield to a signal-to-noise improvement of about 30 dB, bringing the proposed approaches to the level of the most performing sensors for the measurement of vibrations.

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