scholarly journals Chaos based cryptogrphy (cryptography) and image encryption

2021 ◽  
Author(s):  
Amber S. Nasim
Keyword(s):  
Image Encryption ◽  
Chaos Theory ◽  
Input Signal ◽  
Specific Pattern ◽  
Media Content ◽  
Communication Techniques ◽  
Input Signals ◽  
Chaotic Cryptography ◽  
Cryptographic System ◽  
Computation Algorithms

Chaotic cryptography pronounces the use of chaos theory in specific physical dynamical systems working in chaotic system as measure of communication techniques and computation algorithms to accomplish dissimilar cryptographic tasks in a cryptographic system. We have reviewed some of the recent work on chaos-based cryptography in this piece of work. Cryptography methodologies are critically important for storage of secured media content and transmission over exposed systems, for example, the web. For high security, encryption is one the approach to guard the information from leakage. Image encryption is transformation of image to an inaccurate form so that it can be secured from unauthorized users. To explore application of encryption in time samples pattern, we have recommended a secured approach to code input signals by introducing a new encryption algorithm. The algorithm mechanism is such that the transmitter, an input signal was received and coded into a lengthier series of numbers. At the receiver, the coded signal by the transmitter was received and changed back into its original values. This was done based on the idea that the hidden input signal samples using a specific pattern, could only recoverable by a trusted receiver.

scholarly journals Chaos based cryptogrphy (cryptography) and image encryption

2021 ◽  
Author(s):  
Amber S. Nasim
Keyword(s):  
Image Encryption ◽  
Chaos Theory ◽  
Input Signal ◽  
Specific Pattern ◽  
Media Content ◽  
Communication Techniques ◽  
Input Signals ◽  
Chaotic Cryptography ◽  
Cryptographic System ◽  
Computation Algorithms

Chaotic cryptography pronounces the use of chaos theory in specific physical dynamical systems working in chaotic system as measure of communication techniques and computation algorithms to accomplish dissimilar cryptographic tasks in a cryptographic system. We have reviewed some of the recent work on chaos-based cryptography in this piece of work. Cryptography methodologies are critically important for storage of secured media content and transmission over exposed systems, for example, the web. For high security, encryption is one the approach to guard the information from leakage. Image encryption is transformation of image to an inaccurate form so that it can be secured from unauthorized users. To explore application of encryption in time samples pattern, we have recommended a secured approach to code input signals by introducing a new encryption algorithm. The algorithm mechanism is such that the transmitter, an input signal was received and coded into a lengthier series of numbers. At the receiver, the coded signal by the transmitter was received and changed back into its original values. This was done based on the idea that the hidden input signal samples using a specific pattern, could only recoverable by a trusted receiver.

A Novel Iterated Function System-Based Model for Coloured Image Encryption

2021 ◽  
Vol 12 (2) ◽  
pp. 1-10
Author(s):  
Amine Rahmani
Keyword(s):  
Image Encryption ◽  
Iterated Function System ◽  
Mathematical Concept ◽  
Logistic Equation ◽  
Encryption Scheme ◽  
Symmetric Encryption ◽  
New Model ◽  
Proposed Model ◽  
Iterated Function ◽  
Chaotic Cryptography

Chaotic cryptography has been a well-studied domain over the last few years. Many works have been done, and the researchers are still getting benefit from this incredible mathematical concept. This paper proposes a new model for coloured image encryption using simple but efficient chaotic equations. The proposed model consists of a symmetric encryption scheme in which it uses the logistic equation to generate secrete keys then an affine recursive transformation to encrypt pixels' values. The experimentations show good results, and theoretic discussion proves the efficiency of the proposed model.

The Application of Grey Prediction on the Fast Control Power Supply in EAST

2013 ◽  
Vol 427-429 ◽  
pp. 1739-1742
Author(s):  
Hai Hong Huang ◽  
Jia Miao ◽  
Hai Xin Wang ◽  
Feng Feng Wang
Keyword(s):  
Input Signal ◽  
Power Supply ◽  
Grey Theory ◽  
Grey Prediction ◽  
Grey System ◽  
Control Power ◽  
Input Signals ◽  
Simulation And Experiment ◽  
One Step ◽  
Fast Control

Based on the grey theory, a novel model is built to predict the input signal of fast control power supply used in Experimental Advanced Superconducting Tokamak (EAST). The model can be used as online metabolic grey filtering and one-step prediction of different input signals. Results of simulation and experiment show that the predicting algorithm based on the grey system model can predict the input signal primarily.

On a Certain Class of Expanding Systems

2010 ◽  
Vol 17 (2) ◽  
pp. 299-306
Author(s):  
Adam Żuchowski
Keyword(s):  
Transfer Function ◽  
Input Signal ◽  
Initial Conditions ◽  
System Optimization ◽  
Gain Coefficient ◽  
Time Intervals ◽  
System Parameters ◽  
Linear Dynamic ◽  
Subsequent Time ◽  
Input Signals

On a Certain Class of Expanding Systems The interesting properties of a class of expanding systems are discussed. The operation of the considered systems can be described as follows: the input signal is processed by a linear dynamic converter in subsequent time intervals, each of them is equal to Ti. Processing starts at the moments n · Ti, always after zeroing of converter initial conditions. For smooth input signals and a given transfer function of the converter one can suitably choose Ti and the gain coefficient in order to realize the postulated linear operations on input signals, which is quite different comparing it to the operation realized by the converter. The errors of postulated operations are mainly caused by non-smooth components of the input signal. The principles for choice of system parameters and rules for system optimization are presented in the paper. The referring examples are attached too.

Application of Dynamic Input Shaping for a Dual-Mirror System

2021 ◽  
Author(s):  
Alicia Dautt-Silva ◽  
Raymond de Callafon
Keyword(s):  
Input Signal ◽  
Inverse Kinematic ◽  
Open Loop ◽  
Mirror System ◽  
Image Motion ◽  
Step Response ◽  
Input Shaping ◽  
Input Signals ◽  
Compensation Device ◽  
Operating Constraints

Abstract The task of trajectory planning for a dual-mirror optical pointing system greatly benefits from carefully designed dynamic input signals. This paper summarizes the application of multivariable input shaping (IS) for a dual-mirror system, starting from initial open-loop step-response data. The optical pointing system presented consists of two Fast Steering Mirrors (FSM) for which dynamically coupled input signals are designed, while adhering to mechanical and input signal constraints. For the solution, the planned trajectories for the dual-mirrors are determined via (inverse) kinematic analysis. A linear program (LP) problem is used to compute the dynamic input signal for each of the FSMs, with one of the mirrors acting as an image motion compensation device that guarantees tracking of a planned trajectory within a specified accuracy and the operating constraints of the FSMs.

scholarly journals A Novel Adaptive LMS Algorithm with Genetic Search Capabilities for System Identification of Adaptive FIR and IIR Filters

Information ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 176 ◽  
Author(s):  
Amjad J. Humaidi ◽  
Ibraheem Kasim Ibraheem ◽  
Ahmed R. Ajel
Keyword(s):  
System Identification ◽  
Input Signal ◽  
Digital Filters ◽  
Learning Algorithm ◽  
Search Space ◽  
Lms Algorithm ◽  
Adaptation Algorithm ◽  
Genetic Search ◽  
Mutation Operators ◽  
Input Signals

In this paper we introduce a novel adaptation algorithm for adaptive filtering of FIR and IIR digital filters within the context of system identification. The standard LMS algorithm is hybridized with GA (Genetic Algorithm) to obtain a new integrated learning algorithm, namely, LMS-GA. The main aim of the proposed learning tool is to evade local minima, a common problem in standard LMS algorithm and its variants and approaching the global minimum by calculating the optimum parameters of the weights vector when just estimated data are accessible. In the proposed LMS-GA technique, first, it works as the standard LMS algorithm and calculates the optimum filter coefficients that minimize the mean square error, once the standard LMS algorithm gets stuck in local minimum, the LMS-GA switches to GA to update the filter coefficients and explore new region in the search space by applying the cross-over and mutation operators. The proposed LMS-GA is tested under different conditions of the input signal like input signals with colored characteristics, i.e., correlated input signals and investigated on FIR adaptive filter using the power spectral density of the input signal and the Fourier-transform of the input’s correlation matrix. Demonstrations via simulations on system identification of IIR and FIR adaptive digital filters revealed the effectiveness of the proposed LMS-GA under input signals with different characteristics.

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