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Q-processors for real-time image processing

机译:用于实时图像处理的Q处理器

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摘要

In the paper was considered increase of processors performance for solution of image recognition and images analysis (IRIA) problems is very actual for applied mathematics and related branches of science and technology, where the progress is achieved by real-time scale (RTS). The paper presents the main developments of the authors in a such vital and immortal for functioning of Q-processors problems as organization, comparative analysis of QQ-transformation (QQT) structure an neurolike structure, completeness and sufficient of Q-characteristics decomposition, algorithms of image restoration from the set of its Q-characteristics, noise-immunity and information content of QQT, result of comparative mathematical modeling, etc. Which are suggested in a number of papers, however, the analysis, performed in our paper, of certain problems dealing with methodology of generalized Q-transformation. Extreme simplicity of hardware realization provides achievement of maximum possible parallelism of data processing at minimum values of energy consumption and dimension- weight characteristics
机译:在本文中被认为是对图像识别和图像分析的解决方案的性能的增加(IRIA)问题对于应用数学和科学技术分支的问题非常实际,其中通过实时规模(RTS)实现的进展。本文介绍了作者在这种重要性和不朽的主要发展中,Q-处理器问题作为组织的问题,QQ转化(QQT)结构的比较分析是神经化的结构,完整性和Q特征分解,算法图像恢复从其Q-特征,噪声免疫和QQT的信息含量,比较数学建模的结果等,然而,在许多文件中提出的,在我们论文中进行了某些问题处理广义Q转换的方法论。硬件实现的极端简单性提供了在能量消耗和尺寸重量特征的最小值下实现数据处理的最大可能并行性的实现

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