A Method to Extend Orthogonal Latin Square Codes - 2014


Error correction codes (ECCs) are commonly used to safeguard recollections from errors. As multibit errors become more frequent, single error correction codes don't seem to be enough and more advanced ECCs are needed. The use of advanced ECCs in recollections is, however, restricted by their decoding complexity. In this context, one-step majority logic decodable (OS-MLD) codes are an fascinating choice because the decoding is straightforward and can be implemented with low delay. Orthogonal Latin squares (OLS) codes are OS-MLD and are recently thought-about to guard caches and recollections. The main advantage of OLS codes is that they supply a wide selection of choices for the block size and the error correction capabilities. In this transient, a technique to extend OLS codes is presented. The proposed methodology enables the extension of the info block size which will be protected with a given variety of parity bits so reducing the overhead. The extended codes are OS-MLD and have the same decoding complexity to that of the initial OLS codes. The proposed codes have been implemented to guage the circuit area and delay required for various block sizes.

Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE : RDMN: A Relative Density Measure Based on MST Neighborhood for Clustering Multi-Scale Datasets ABSTRACT: Techniques for discovering intrinsic clusters that are based on density do so by classifying the regions
PROJECT TITLE : LTC: a Fast Algorithm to Accurately Find Significant Items in Data Streams ABSTRACT: Finding the top k most frequent items in databases has been a contentious issue recently. The problem of locating the top-k persistent
PROJECT TITLE : Ontology-Based Privacy Data Chain Disclosure Discovery Method for Big Data ABSTRACT: Cloud computing and big data have quickly become the most popular forms of computing and data resources because of their ability
PROJECT TITLE : Optimizing Gradient Methods for IoT Applications ABSTRACT: The successful resolution of problems involving linear programming (LP) and nonlinear programming (NLP) is significant because of the breadth of their
PROJECT TITLE : Short-Term Traffic Flow Forecasting Method With M-B-LSTM Hybrid Network ABSTRACT: Recently, good results in short-term traffic forecasting have been achieved through the use of deep learning. Nevertheless, the

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry