Watermarking is the process of embedding the particular information into the audio signal for managing the ownership copyrights through wireless network. During the watermarking process, the audio signal consumes high...
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Watermarking is the process of embedding the particular information into the audio signal for managing the ownership copyrights through wireless network. During the watermarking process, the audio signal consumes high energy, conflicting problem of robustness and imperceptibility, signal to noise ratio, bit error rate and normalized correlation. To overcome these issues present in the audio watermarking process, novel wavelet decomposition and evolutionary algorithm is utilized. Initially the input information or message has been split into two and the spillted message is watermarked using the audio and the image in wireless network. The first half of the message is watermarked with the help of the image and the next half of the image is watermarked by audio. Initially the watermarked image is transferred into YIQ image, from the transferred image the scrambled image is generated with the help of the Hidden Markov tree counter let wavelet transform method for generating the watermarking image. Then the next part of information is watermarked by audio signal which is decomposed into various sub bands using the Multi-resolution complex dual tree wavelet method. From the decomposed audio signal, the message authentication code based watermarks have been embedded in the lower frequency coefficients. Then the embedded process is performed by using the Dead zone quantization process which is optimized with the help of the fireflies algorithm for enhancing the quality of the watermarking process. Finally both watermarking process is embedded for improving the security to the information with efficient manner through wireless network. In addition the efficient watermarking process through wireless network reduces the various attacks while extracting the water marker. Thus the optimized wavelet and quantization process improves the image and audio watermarking through wireless network and efficiency of the proposed system is evaluated using the experimental results in terms
This paper mainly deals with Bio Inspired which means biological structures. Bio Inspired easily handle failure which determines the real-world complicated engineering issues. It continually finds the optimum resoluti...
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This paper mainly deals with Bio Inspired which means biological structures. Bio Inspired easily handle failure which determines the real-world complicated engineering issues. It continually finds the optimum resolution to unravel its drawback maintaining good balance among its parts. Widen the range and growth of Bio Inspired algorithms analyze new fields of application. A disaster is a sudden, disastrous event that seriously disrupts the functioning of a community or society and causes human, material, and economic or environmental losses that exceed the community’s or society’s ability to cope using its own resources. This paper presents comparative study between ant colony optimization algorithm and fireflies algorithm to find shortest route during disaster. ACO is inspired by behavior of ants. The specialty of ACO algorithm is to find finest route with respect to each road’s length and damage degree. ACO provides reliable paths and also the decision is based on pheromone level released by ants. One of the recent developed swarm intelligence algorithm is firefly algorithm introduced by Yang. This algorithm inspired by behavior of insects. It works based on three rule: They are unisex, attractiveness and brightness. So these two algorithms helps in finding the shortest path between origin point and destination point.
Six modern and promising evolutionary algorithms are described: genetic algorithm, differential evolution method, variational genetic algorithm, particle swarm optimization algorithm, bat-inspired method and firefly a...
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Six modern and promising evolutionary algorithms are described: genetic algorithm, differential evolution method, variational genetic algorithm, particle swarm optimization algorithm, bat-inspired method and firefly algorithm. For all algorithms brief description and main steps of receiving solution are given. In the experimental part all algorithms are compared by the effectiveness of solving the parametric optimization problem for PID controllers. (C) 2017 The Authors. Published by Elsevier B.V.
Six modern and promising evolutionary algorithms are described: genetic algorithm, differential evolution method, variational genetic algorithm, particle swarm optimization algorithm, bat-inspired method and firefly a...
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Six modern and promising evolutionary algorithms are described: genetic algorithm, differential evolution method, variational genetic algorithm, particle swarm optimization algorithm, bat-inspired method and firefly algorithm. For all algorithms brief description and main steps of receiving solution are given. In the experimental part all algorithms are compared by the effectiveness of solving the parametric optimization problem for PID controllers.
Firefly algorithm, a new type of swarm intelligence in optimization, has a good performance in combinatorial optimization problem. For Traveling Salesmen Problem(TSP), this process proposes an optimized path approach ...
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ISBN:
(纸本)9781510819085
Firefly algorithm, a new type of swarm intelligence in optimization, has a good performance in combinatorial optimization problem. For Traveling Salesmen Problem(TSP), this process proposes an optimized path approach based on the modified firefly algorithm. In order to avoid a local optimum, an elitist strategy combined with mutation mechanism and the mechanism of fluorescence change are used to help the fireflies group go out of the local optimal area. For problems on intersection of sets, C2Opt operator can be used on the global optimization of the path. Finally, the experimental result would be compared with other classical algorithm to verify the reliability via TSPLIB instance test.
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