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Hamming Code for Double Bit Error Detection & Rectification Capability by Using Cadence Tool
M. Narasimharao1, Telagarapu. Prabhakar2, K. Satya Kiran3
1M. Narasimha Rao, Department of ECE, GMR Institute of Technology, GMR Nagar, Rajam, Srikakulam District, Andhra Pradesh, India.
2Dr. T. Prabhakar Department of ECE, GMR Institute of Technology, GMR Nagar, Rajam, Srikakulam District, Andhra Pradesh, India.
3K. Satya Kiran Department of ECE, GMR Institute of Technology, GMR Nagar, Rajam, Srikakulam District, Andhra Pradesh, India.
Manuscript received on 02 June 2019 | Revised Manuscript received on 10 June 2019 | Manuscript published on 30 June 2019 | PP: 1720-1726 | Volume-8 Issue-8, June 2019 | Retrieval Number: H6702068819/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Error free transformation is a major issue in present Electronic circuits. Fixed data transmission from sender to receiver occurring greater issue, i.e. errors in information of data transmission from transmitter to receiver. In the digital communication systems, digital code may be distorted during transmission, which can show to the inaccurate information response of the receiver. Here Error correction codes used to protect the information In memories and logic registers in electronic circuits. Hamming codes are one of the best errors, correcting code either, even parity or odd parity check method. In this project Hamming code algorithm is used for Errors detection and Error rectification. The Hamming codes will be implemented in Xilinx & Cadence, At the receiver information is recovered to get original 15 bit information signal data. In which 15bit information data will be transmitted with 4 bit redundant two Error value bits. At the receiver is recovered to get 11 bit data (input data).
Keywords: Hamming Code, Error Detection, Error Correction, Cadence Tool.

Scope of the Article: Data Mining Methods, Techniques, and Tools