reconfigurable memory
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Author(s):  
R. Amirtha Varshini Et.al

Histogram computation is the crucial task used in processing so many image guided applications like pattern recognition, image segmentation etc. Image registration is one of the fundamental techniques for pre-processing of the images. Registration is the process of overlaying multiple images to geometrically align them. In medical Image processing, the improper registration can have negative impact on the analysis of the image which influences the final diagnosis. The accurate result of image registration is obtained by matching of multimodal images. Mutual Information is one of the commonly used techniques to find the similarity measurement between multi-modal images. Measurement of similarity requires a computation of histogram of individual images and joint histogram between the images. The hardware implementation of histogram computation has advantages in terms of flexible design, low power consumption, high speed, less execution time than the software implementation. This paper proposed a parallel algorithm for histogram computation. A memory based pipeline architecture is designed for implementing the proposed algorithm. The hardware mapping of the algorithm on FPGA is proposed and simulating them using Xilinx software tools.


Author(s):  
Hung-Ming Chen ◽  
Chia-Lin Hu ◽  
Kang-Yu Chang ◽  
Alexandra Küster ◽  
Yu-Hsien Lin ◽  
...  

Author(s):  
Bing Wu ◽  
Dan Feng ◽  
Wei Tong ◽  
Jingning Liu ◽  
Chengning Wang ◽  
...  

2020 ◽  
Vol E103.D (3) ◽  
pp. 578-589
Author(s):  
Jun IWAMOTO ◽  
Yuma KIKUTANI ◽  
Renyuan ZHANG ◽  
Yasuhiko NAKASHIMA

As the technology is improving, channel length of MOSFET is scaling down. In this environment stability of SRAM becomes the major concern for future technology. Static noise margin (SNM) plays a vital role in stability of SRAM. This paper gives an introduction to the reconfigurable memory and 6T SRAM cell. It includes the implementation, characterization and analysis of reconfigurable memory cell and its comparison with the conventional 6T SRAM cell for various parameters like read margin, write margin, data retention voltage, temperature and power supply fluctuations and depending upon these analysis we find SNM for 6T and 8T SRAM cell. The tool used for simulation purpose is IC Station by Mentor Graphics using 350nm technology at supply voltage of 2.5volts.


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