RETRACTED ARTICLE: Image compression using optimized wavelet filter derived from grey wolf algorithm

Ravi, Renjith V.; Subramaniam, Kamalraj

doi:10.1007/s12652-020-02290-7

Cited by 8 publications

(3 citation statements)

References 31 publications

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“…1 They have been widely used in speech signal processing, fault detection, biomedical engineering, and other fields. [2][3][4][5] Among them, the need for ultra-low power biomedical signal analysis represented by the electronic cochlea, implantable cardiac pacemakers, and wearable dynamic electroencephalogram systems has promoted the development of analog wavelet filters. [6][7][8] However, with the continuous expansion of research objects and scopes, the limitations of analog wavelet filters in dealing with some problems are gradually exposed.…”

Section: Introductionmentioning

confidence: 99%

“…Shi et al 16 pointed out that using a more general fractional domain plane can effectively analyze frequency-domain energy nonoptimal aggregated signals. As a generalized form of 1 Key Laboratory of Hunan Province on Information Photonics and Freespace Optical Communications, Hunan Institute of Science and Technology, Yueyang, China 2 College of Physics and Electronics, Hunan Institute of Science and Technology, Yueyang, China 3 School of Mathematics and Computer Science, Panzhihua University, Panzhihua, China classical analog wavelet filters, fractional-order analog wavelet filters extend the time-frequency domain plane in the traditional wavelet theory to the time-fractional domain plane. Therefore, they not only inherit many advantages of traditional wavelet filters, such as linear characteristics, multiresolution analysis but also have the characterization function of the fractional domain.…”

Section: Introductionmentioning

confidence: 99%

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Design of a class of fractional-order analog wavelet filters

Li,

Zou,

Feng

et al. 2023

Journal of Algorithms & Computational Technology

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In this article, a methodology is proposed to implement fractional-order analog wavelet filters in the frequency domain. Under the proposed scheme, the fractional-order transfer function of the linear time-invariant system is used to approximate the Gaussian-like wavelet functions. Firstly, we construct a causal, stable, and physically achievable fractional-order mathematical approximation model. Then, the fractional-order mathematical approximation model is transformed into an optimization problem, and a hybrid particle swarm optimization algorithm is exploited to find its global optimal solution. At the same time, constraint terms are introduced to ensure the desired stability. The simulation results show that the fractional-order analog wavelet filters have higher approximation accuracy than the traditional integer-order analog wavelet filters. Furthermore, fractional-order analog wavelet filters can provide more precise control of the stopband attenuation rate, which is a key issue for many engineering applications.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Design of a class of fractional-order analog wavelet filters

Li,

Zou,

Feng

et al. 2023

Journal of Algorithms & Computational Technology

View full text Add to dashboard Cite

show abstract

“…On the other hand, blockchain technology development as well as implementation in SCM is in the toddler stage and it has to overcome numerous challenges for achieving a high degree of security 13–17 . The optimization algorithms have undergone diverse improvements and modifications to solve complex problems 18–20 . There are a limited number of transactions that can be dealt within a short period of time to maintain a high degree of security.…”

Section: Introductionmentioning

confidence: 99%

Blockchain‐based secure information sharing for supply chain management: Optimization assisted data sanitization process

et al. 2020

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Currently, the furious competitiveness in global markets and speedy improvements in information technology lead to shorter product life cycles, lesser transportation capabilities, and increased demands as well. In most business scenarios, the supply chain network is becoming one of the most vital focusing areas. In the supply chain network, blockchain technology is a promising solution for secure information sharing. However, it is a bit critical in maintaining security at each level of the blockchain and hence the public-private-key cryptography is more commonly preferred. This study intends to construct a new privacy preservation model in the field of supply chain networks based on blockchain technology by undergoing three major phases, namely, (a) data sanitization, (b) key generation, and (c) restoration. Further, the sensitive fields in the original data are selected during the data sanitization phase, and in the key generation phase; the optimal key is generated to hide the selected sensitive fields. The hidden data with the secured key is transferred from the source (manufacturer) to destination (vendor) in the supply chain network via the blockchain. The restoration process takes place in the receiver side with the help of the same key. Among all these data flow methods, the optimal key selection is the critical issue that needs to be overridden to make the data transmission secured. As a novelty, a new optimization algorithm referred to as Whale with New Crosspoint-based Update (WNU), which is the advanced version of Whale Optimization Algorithm (WOA), is developed here to select the optimal key. Finally, the proposed WNU model is analyzed in terms of Hiding Failure (HF) rate, Information Preservation (IP) Rate, and False Rule generation (FR), and Degree of Modification (DM). The proposed secured information sharing in supply chain management (SCM) with blockchain technology will be validated by comparing it over the traditional models in terms of security as well.

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Optimal feature selection with hybrid classification for automatic face shape classification using fitness sorted Grey wolf update

Sukumaran

Brindha

2021

Multimed Tools Appl

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RETRACTED ARTICLE: Image compression using optimized wavelet filter derived from grey wolf algorithm

Cited by 8 publications

References 31 publications

Design of a class of fractional-order analog wavelet filters

Design of a class of fractional-order analog wavelet filters

Blockchain‐based secure information sharing for supply chain management: Optimization assisted data sanitization process

Optimal feature selection with hybrid classification for automatic face shape classification using fitness sorted Grey wolf update

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