Mustafa Alçi

Using an adaptive neuro-fuzzy inference system-based interpolant for impulsive noise suppression from highly distorted images

A new impulsive noise (IN) suppression filter, entitled Adaptive neuro-fuzzy inference system (ANFIS)-based impulsive noise suppression Filter, which shows a high performance at the restoration of images distorted by IN, is proposed in this paper. The extensive simulation results show that the proposed filter achieves a superior performance to the other filters mentioned in this paper in the cases of being effective in noise suppression and detail preservation, especially when the noise density is very high.

A SC-CNN-Based Chaotic Masking System with Feedback

A secure transmission application of the State Controlled Cellular Neural Network (SC–CNN)-based circuit is presented. Since the SC–CNN-based circuit has feedback connections between the cells, it is potentially very suitable for realizing a chaotic masking system with feedback algorithm. So, we have constructed a chaotic masking system with feedback using the SC–CNN-based circuit. PSpice simulation experiments verify that the proposed SC–CNN-based secure communication system exhibits a good performance for a wide range of amplitude and spectral characteristics of the information signal.

IMPROVED REALIZATION OF MIXED-MODE CHAOTIC CIRCUIT

An improved realization of mixed-mode chaotic circuit which has both autonomous and nonautonomous chaotic dynamics is proposed. Central to this study is inductorless realization of mixed-mode chaotic circuit using FTFN-based inductance simulator. FTFN-based topology used in this realization enables the simulation of ideal floating and grounded inductance. This modification provides an alternative solution to the integration problem of not only mixed-mode chaotic circuit but also other chaotic circuits in the literature using CMOS VLSI technologies. In addition to this major improvement, CFOA-based nonlinear resistor was used in the new realization of mixed-mode chaotic circuit. The usage of CFOA-based nonlinear resistor in the circuits structure reduces the component count and provides buffered and isolated output.

Impulsive Noise Suppression from Highly Corrupted Images by Using Resilient Neural Networks

A new impulsive noise elimination filter, entitled Resilient Neural Network based impulsive noise removing filter (RF), which shows a high performance at the restoration of images corrupted by impulsive noise, is proposed in this paper. The RF uses Chi-square goodness-of-fit test in order to find corrupted pixels more accurately. The corrupted pixels are replaced by new values which were estimated by using the proposed RF. Extensive simulation results show that the proposed filter achieves a superior performance to the other filters mentioned in this paper in the cases of being effective in noise suppression and detail preservation, especially when the noise density is very high.

Impulsive noise suppression from images with the noise exclusive filter

A novel impulsive noise elimination filter, entitled noise exclusive filter (NEF), which shows a high performance at the restoration of images distorted by impulsive noise, is proposed in this paper. NEF uses chi-square goodness-of-fit test in order to detect the corrupted pixels more accurately. Simulation results show that the proposed filter achieves a superior performance compared with the other filters mentioned in this paper in terms of noise suppression and detail preservation, particularly when the noise density is very high. The proposed method also achieves the robustness and detail preservation perfectly for a wide range of impulsive noise density. NEF provides efficient filtering performance with reduced computational complexity.

Impulsive Noise Suppression from Highly Distorted Images with Triangular Interpolants

Summary In this paper a new filter, Triangular Interpolant Based Impulsive Noise Suppression Filter (SF), is proposed to restore images corrupted by fixed valued impulsive noise (IN). The proposed filter comprises two main stages: detection of noise and restoration of corrupted pixels. The SF achieves the restoration of the detected noisy pixels by using one of the Triangular Interpolant techniques and leaves the other pixels unaltered. Simulation results reveal that the proposed filter shows better performance than the highly approved IN suppression filters across a wide noise density ranging from 10% to 90%. The proposed filter also perfectly achieves the robustness and detail preservation with reduced computational complexity.

Using an exact radial basis function artificial neural network for impulsive noise suppression from highly distorted image databases

In this paper, a new filter, RM, which is based on exact radial basis function artificial neural networks, is proposed for the impulsive noise suppression from highly distorted images. The RM uses Chi-Squared based goodness-of-fit test in order to find corrupted pixels more accurately.The proposed filter shows a high performance at the restoration of images distorted by impulsive noise. The extensive simulation results show that the proposed filter achieves a superior performance to the other filters mentioned in this paper in the cases of being effective in noise suppression and detail preservation, especially when the noise density is very high.

A Simple CMOS-Based Membership Function Circuit

In this study, design and analysis of a voltage-input current-output simple CMOS-based Membership Function Circuit (MFC) is presented. The proposed MFC is based on simple OTA structure and current-mode maximum circuits. This MFC implements basic four membership functions (trapezoidal, triangle, Z-shape and S-shape). The characteristics (width, height, slope and position) of the implemented membership functions are easily adjustable and it is suitable for current-mode fuzzy hardware. While the circuits membership function characteristics have been confirmed by PSPICE-DC simulations, the circuits transient response has been analyzed applying up to 10 MHz input signals in continuous time by PSPICE Transient simulations.

MIXED-MODE CHAOTIC CIRCUIT AND ITS APPLICATION TO CHAOTIC COMMUNICATION FOR TRANSMISSION OF ANALOG SIGNALS

We present a mixed-mode chaotic circuit which has both autonomous and nonautonomous chaotic circuit dynamics and we show how this mixed-mode chaotic circuit can be utilized in a chaotic communication system for transmitting analog signals. The investigation of static and dynamic analyses of the proposed circuit has been carried out and its chaotic behavior was verified by PSpice simulation experiments. For the transmission of analog signals via mixed-mode chaotic circuit, a well-known chaotic communication system introduced by Itoh et al. was chosen.

EXPERIMENTAL CONFIRMATION OF SC-CNN-BASED CHAOTIC MASKING SYSTEM

In this study experimental results of State Controlled Cellular Neural Network (SC-CNN)-based chaotic masking system are presented. By means of this study, the chaotic masking system with feedback algorithm in SC-CNN-based circuit is experimentally proved.