Critical block analysis for the transfer, gain and phase functions in multiple-loop feedback networks

1978 ◽  
Vol 6 (1) ◽  
pp. 89-104 ◽  
Author(s):  
C. Acar ◽  
M. S. Ghausi ◽  
K. R. Laker
Author(s):  
K.R. Shankarkumar ◽  
Gokul Kumar

: 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.


2010 ◽  
Vol 139-141 ◽  
pp. 1889-1893 ◽  
Author(s):  
Peng Fei Wang ◽  
Dian Hua Zhang ◽  
Xu Li ◽  
Jia Wei Liu

In order to improve the flatness of cold rolled strips, strategies of closed loop feedback flatness control and rolling force feed forward control were established respectively, based on actuator efficiency factors. As the basis of flatness control system, efficiencies of flatness actuators provide a quantitative description to the law of flatness control. For the purpose of obtaining accurate efficiency factors matrixes of actuators, a self-learning model of actuator efficiency factors was established. The precision of actuator efficiency factors could be improved continuously by correlative measurement flatness data inputs. Meanwhile, the self-learning model of actuator efficiency factors permits the application of this flatness control for all possible types of actuators and every stand type. The developed flatness control system has been applied to a 1250mm single stand 6-H reversible UCM cold mill. Applications show that the flatness control system based on actuator efficiency factors is capable to obtain good flatness.


Lab on a Chip ◽  
2021 ◽  
Author(s):  
Ningquan Wang ◽  
Ruxiu Liu ◽  
Norh Asmare ◽  
Chia-Heng Chu ◽  
Ozgun Civelekoglu ◽  
...  

An adaptive microfluidic system changing its operational state in real-time based on cell measurements through an on-chip electrical sensor network.


Small Science ◽  
2021 ◽  
pp. 2100002
Author(s):  
Tomohito Sekine ◽  
Yi-Fei Wang ◽  
Jinseo Hong ◽  
Yasunori Takeda ◽  
Reo Miura ◽  
...  

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