Open Access. Powered by Scholars. Published by Universities.®

Engineering Commons

Open Access. Powered by Scholars. Published by Universities.®

Computer Sciences

PDF

2010

Chaos

Articles 1 - 2 of 2

Full-Text Articles in Engineering

Programmable Design And Implementation Of A Chaotic System Utilizing Multiple Nonlinear Functions, Recai̇ Kiliç, Fatma Yildirim Dalkiran Jan 2010

Programmable Design And Implementation Of A Chaotic System Utilizing Multiple Nonlinear Functions, Recai̇ Kiliç, Fatma Yildirim Dalkiran

Turkish Journal of Electrical Engineering and Computer Sciences

In addition to exhibiting a rich variety of bifurcation and chaos via tuning parameters, a chaotic system introduced by Sprott can be modeled and realized with a fixed main system block and many different changeable nonlinear function blocks such as piecewise-linear function, cubic function and other trigonometric functions. This system is very suitable for implementing a programmable chaos generator according to its changeable nonlinearity. This paper presents a FPAA (Field Programmable Analog Array)-based programmable implementation of this system. Nonlinear function blocks used in this chaotic system are modeled with FPAA programming and a model is rapidly changed for realizing other …


Artificial Neural Network Based Chaotic Generator For Cryptology, İlker Dalkiran, Kenan Danişman Jan 2010

Artificial Neural Network Based Chaotic Generator For Cryptology, İlker Dalkiran, Kenan Danişman

Turkish Journal of Electrical Engineering and Computer Sciences

Chaotic systems are sensitive to initial conditions, system parameters and topological transitivity and these properties are also remarkable for cryptanalysts. Noise like behavior of chaotic systems is the main reason of using these systems in cryptology. However some properties of chaotic systems such as synchronization, fewness of parameters etc. cause serious problems for cryptology. In this paper, to overcome disadvantages of chaotic systems, the dynamics of Chua's circuit namely x, y and z were modeled using Artificial Neural Network (ANN). ANNs have some distinctive capabilities like learning from experiences, generalizing from a few data and nonlinear relationship between inputs and …