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String matching is a classical problem in computer science. After the study of the Naïve string search, Brute Force and the KMP algorithm, several advantages and disadvantages of the algorithms have been analyzed. Considering KMP in particular concept of parallelization has been introduced to improve the performance of the KMP algorithm. The algorithm is(More)
Bit Parallelism exploits bit level parallelism in hardware to perform operations. Bit Parallelism is a technique that is used to solve string matching problem, when the pattern to be searched for is less than or equal word size of a system. It is a technique that takes the advantage of intrinsic parallelism of the bit operations inside a system word. By(More)
Pattern matching is a crucial task in several critical network services such as intrusion detection. In this paper we present an efficient implementation of the DFA with optimized area and optimized memory by the introduction of state minimization algorithm. By using minimized DFA the clock frequency reduces to 40% of the original and the area also reduces(More)
String matching plays an important role in field of Computer Science and there are many algorithm of String matching, the important aspect is that which algorithm is to be used in which condition. BM(Boyer-Moore) algorithm is standard benchmark of string matching algorithm so here we explain the BM(Boyer-Moore) algorithm and then explain its improvement as(More)
Activation function is the most important function in neural network processing. In this article, the field-programmable gate array (FPGA)-based hardware implementation of a multilayer feed-forward neural network, with a log sigmoid activation function and a tangent sigmoid (hyperbolic tangent) activation function has been presented, with more accuracy than(More)
Aho-Corasick is a standard string matching algorithm. It can match multiple patterns simultaneously and affirmed deterministic performance under all circumstances. AhoCorasick feed solutions to various real world applications like intrusion detection systems, text mining, search engine, multimedia and computational biology. In order to improve performance(More)
Big data is a term used for very large data sets that have more varied and complex structure. These characteristics usually correlate with additional difficulties in storing, analyzing and applying further procedures or extracting results. Big data analytics is the term used to describe the process of researching massive amounts of complex data in order to(More)