Low-Power Low-Area architecture of Probability Density Function Estimation for Histogram Equalization

Authors

  • Koteswar Rao Bonagiri  Research scholar, Department of Electronics and Communication Engineering, Jawaharlal Nehru Technological University, Hyderabad, India
  • Giri Babu Kande  Assistant Proffesor, Marrilaxman Reddy institute of Technology and Management, Hyderabad, India,
  • P. Chandrasekhar Reddy  Professor, Department of Electronics and Communication Engineering, Vasireddy Venkatadri Institute of Technology, Andhra Pradesh, India

DOI:

https://doi.org/10.32628/IJSRST218658

Keywords:

Probability density function, Look-Up Table, Carry Select Adder, Field Programmable Gate Array and Application Specified Integrated Chip.

Abstract

Estimation of Probability Density Functions (PDFs) in view of accessible information is critical issue emerging in various fields, for example, broadcast communications, machine learning, information mining, design pattern recognition and Personal Computer (PC) vision. In this paper, the Look-Up Table–Carry Select Adder-PDF (LUT-CSLA-PDF) mehod is implemented to increase system performance. The LUT is one of the fast way to recognize a complex function in the digital logic circuit. In this work, The FPGA (field programmable gate array) analysis, LUT, slices, flip flops, frequency are improved as well as ASIC (application specified integrated chip) implementation analysis an area, power, delay, Area Power Product (APP), Area Delay Product (ADP) are enhanced in LUT-CSLA-PDF technique compared to conventional methods.

References

  1. Pokrajac, Dragoljub, et al. "Variable Width Elliptic Gaussian Kernels for Probability Density Estimation." Telecommunications in Modern Satellite, Cable and Broadcasting Services, 2007. TELSIKS 2007. 8th International Conference on. IEEE, 2007.
  2. Carbone, P., and D. Petri. "Non-parametric estimation of probability density functions via a simple interpolation filter." Instrumentation and Measurement Technology Conference (I2MTC), 2015 IEEE International. IEEE, 2015.
  3. Pana, Cristian, Stefano Severi, and Giuseppe Thadeu Freitas de Abreu. "An adaptive approach to non-parametric estimation of dynamic probability density functions." Positioning, Navigation and Communications (WPNC), 2016 13th Workshop on. IEEE, 2016.
  4. Bernotas, Marius, and Charles Nelson. "Probability density function analysis for optimization of underwater optical communications systems." OCEANS'15 MTS/IEEE Washington. IEEE, 2015.
  5. Hanebeck, Uwe D. "Kernel-based deterministic blue-noise sampling of arbitrary probability density functions." Information Sciences and Systems (CISS), 2014 48th Annual Conference on. IEEE, 2014.
  6. Wang, Lingzhi, Fucai Qian, and Jun Liu. "Shape control on probability density function in stochastic systems." Journal of Systems Engineering and Electronics 25.1 (2014): 144-149.
  7. Yin, Liping, Hongyan Zhang, and Lei Guo. "Data driven O/P joint probability density function control for multivariate non-linear non-Gaussian systems." IET Control Theory & Applications 9.18 (2015): 2697-2703.
  8. Hai-Yan, Luan, and Jiang Hua. "Vicinal risk minimization-based probability density function estimation algorithm using SVM." Information and Computing (ICIC), 2010 Third International Conference on. Vol. 4. IEEE, 2010.
  9. Yu, Bo, et al. "Modeling MOSFET drain current non-Gaussian distribution with power-normal probability density function." IEEE Electron Device Letters 35.2 (2014): 154-156.
  10. Agarwal, Rahul, Zhe Chen, and Sridevi V. Sarma. "A Novel Nonparametric Maximum Likelihood Estimator for Probability Density Functions." IEEE transactions on pattern analysis and machine intelligence 39.7 (2017): 1294-1308.
  11. Ren, Weilong. "A Novel Asymmetrical Probability Density Function for Modeling Log-Ratio SAR Images." IEEE Geoscience and Remote Sensing Letters 13.3 (2016): 369-373.
  12. Komaty, Ali. "EMD-based filtering using similarity measure between probability density functions of IMFs." IEEE Transactions on Instrumentation and Measurement 63.1 (2014): 27-34.
  13. Liu, Yu, Hong Wang, and Chaohuan Hou. "Sliding-mode control design for nonlinear systems using probability density function shaping." IEEE transactions on neural networks and learning systems 25.2 (2014): 332-343.
  14. Cui, Guolong, et al. "Exact Distribution for the Product of Two Correlated Gaussian Random Variables." IEEE Signal Processing Letters 23.11 (2016): 1662-1666.
  15. Berisha, Visar, and Alfred O. Hero. "Empirical non-parametric estimation of the fisher information." IEEE Signal Processing Letters 22.7 (2015): 988-992.

International Journal of Scientific Research in Science and Technology

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Published

2021-12-30

Issue

Volume 8, Issue 6, November-December-2021

Section

Research Articles

License

Copyright (c) IJSRST

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Koteswar Rao Bonagiri, Giri Babu Kande, P. Chandrasekhar Reddy "Low-Power Low-Area architecture of Probability Density Function Estimation for Histogram Equalization" International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011,Volume 8, Issue 6, pp.418-427, November-December-2021. Available at doi : https://doi.org/10.32628/IJSRST218658