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This paper presents and investigates a method named M×N‐ary chaotic pulse‐width‐position modulation (CPWPM) which is based on the combination of M‐ary chaotic pulse‐position modulation (CPPM) and N‐ary chaotic pulse‐width modulation (CPWM) in order to provide a better performance in noise‐affected environments as well as improve significantly bit rate.

Analysis of schemes for modulator and demodulator are presented in detail through describing the schemes of the individual methods and their combination. Theoretical evaluation of bit‐error rate (BER) performance in presence of additive white Gaussian noise (AWGN) is provided. Chaotic behavior with tent map in variation of modulation parameters is also investigated. In order to verify the theoretical analyses, numerical simulations are carried out and their results are reported.

Both evaluation and simulation results show that when the number of symbols increases, the bit rate is improved significantly but the BER performance is just slightly worse. This makes M×N‐ary CPWPM become an effective method for chaos‐based digital communication.

Although CPPM, CPWM and M‐ary modulation methods have been described in the literature separately, their combination is presented and investigated for the first time in this paper.

An image contrast enhancement is one of the most important low‐level image pre‐processing tasks required by the vision‐based advanced driver assistance systems (ADAS). This paper seeks to address this important issue keeping the real time constraints in focus, which is especially vital for the ADAS.

The approach is based on a paradigm of nonlinear‐coupled oscillators in image processing. Each layer of the colored images is treated as an independent grayscale image and is processed separately by the paradigm. The pixels with the lowest and the highest gray levels are chosen and their difference is enhanced to span all the gray levels in an image over the entire gray level range, i.e. [0 1]. This operation enhances the contrast in each layer and the enhanced layers are finally combined to produce a color image of a much improved quality.

The approach performs robust contrast enhancement as compared to other approaches available in the relevant literature. Generally, other approaches do need a new setting of parameters for every new image to perform its task, i.e. contrast enhancement. These approaches are not useful for real‐time applications such as ADAS. Whereas, the proposed approach presented in this paper performs contrast enhancement for different images under the same setting of parameters, hence giving rise to the robustness in the system. The unique setting of parameters is derived through a bifurcation analysis explained in the paper.

The proposed approach is novel in different aspects. First, the proposed paradigm comprises of coupled differential equations, and therefore, offers a continuous model as opposed to other approaches in the relevant literature. This continuity in the model is an inherent feature of the proposed approach, which could be useful in realizing real‐time image processing with an analog implemented circuit of the approach. Furthermore, a novel framework combining coupled oscillatory paradigm and cellular neural network is also possible to achieve ultra‐fast solution in image contrast enhancement.