نتایج جستجو برای: varying terms
تعداد نتایج: 646378 فیلتر نتایج به سال:
In this paper, linear matrix inequality (LMI) approach for synchronization of chaotic fuzzy cellular neural networks (FCNNs) with discrete and unbounded distributed delays based on sampled-data controlis investigated. Lyapunov-Krasovskii functional combining with the input delay approach as well as the free-weighting matrix approach are employed to derive several sufficient criteria in terms of...
The objective of the present study was to prepare controlled release formulation of Moxifloxacin hydrochloride ocular nanoparticles. The nanoparticles were prepared by solvent displacement method using Eudragit RL 100 as a polymer. Different formulations were prepared by varying the ratios of drug and polymer and varying the ratios of organic and aqueous phase. The formulations were evaluated i...
The objective of the present study was to prepare controlled release formulation of Moxifloxacin hydrochloride ocular nanoparticles. The nanoparticles were prepared by solvent displacement method using Eudragit RL 100 as a polymer. Different formulations were prepared by varying the ratios of drug and polymer and varying the ratios of organic and aqueous phase. The formulations were evaluated i...
Fuzzy segmentation is an effective way of segmenting out objects in images containing both random noise and varying illumination. In this paper, a modified method based on the Comprehensive Learning Particle Swarm Optimization (CLPSO) is proposed for pixel classification in HSI color space by selecting a fuzzy classification system with minimum number of fuzzy rules and minimum number of incorr...
Impulsive bidirectional associative memory neural network model with time-varying delays and reaction-diffusion terms is considered. Several sufficient conditions ensuring the existence, uniqueness, and global exponential stability of equilibrium point for the addressed neural network are derived by M-matrix theory, analytic methods, and inequality techniques. Moreover, the exponential converge...
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