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COMPUTATIONAL CHARACTERIZATION OF A HYBRID BIOCHIP (BIOCOMPUTER, MOLECULAR, SIXTH GENERATION COMPUTER, ORGANIC).

机译:混合生物芯片(生物计算机,分子式,第六代计算机,有机)的计算特性。

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摘要

Inherent limitations of conventional silicon-based computing has resulted in much recent research in alternative computing techniques. One such alternative is the "biochip" approach.; A review of current work and literature indicates three groups of biocomputing devices. The first group (usually called implantations) is based on utilizing conventional computing techniques in biomedical applications. The second group is geared towards the synthesis of an organic switch similar to the semiconductor PN switch. The third approach (which includes this research) would utilize computing techniques which are characteristic of living organisms.; This research investigates an architecture designed to utilize the natural computing techniques of parallelism, fuzziness, pattern recognition, and adaptability. A hybrid model combining conventional silicon techniques and natural techniques is proposed. The model consists of a network of silicon controllers and organic transducing tissues. A computer simulation is then developed to investigate the model. Experiments with the simulation confirm the belief that natural techniques can successfully be used to solve a certain class of problems. Simple but suggestive computing tasks were solved with the model. The programming technique used (evolutionary programming) is treated in detail.; The major conclusions of the research are: (1) Conventional silicon computing resources are inefficient at simulating biological processes. Such simulations can however still be advantageously used in solving certain problems. (2) The rigidity and high precision of conventional computing may be relaxed in certain cases. A certain amount of impreciseness can be advantageous in such cases. (3) Silicon and organic computing devices supplement rather than replace each other. (4) Massive parallelism at a low hierarchical level can be used in novel ways which differ from conventional precise operations like matrix multiplications. (5) Simple programming language constructs utilizing natural computing techniques can be implemented as extensions to conventional programming languages. (6) Most of the major obstacles confronting the PN-switch approach to biochip design can be circumvented by the alternative approach of utilizing natural computing techniques. (7) Novel computer architectures can be designed to take advantage of natural computing techniques. (8) Linear topologies may be better than two-dimensional topologies in certain adaptive network applications.
机译:常规的基于硅的计算的固有局限性导致了对替代计算技术的最新研究。一种这样的替代方法是“生物芯片”方法。对当前工作和文献的回顾指出了三组生物计算设备。第一组(通常称为植入)是基于在生物医学应用中利用常规计算技术的。第二组用于合成类似于半导体PN开关的有机开关。第三种方法(包括这项研究)将利用生物体特有的计算技术。这项研究调查了一种旨在利用并行性,模糊性,模式识别和适应性的自然计算技术的体系结构。提出了一种结合了常规硅技术和自然技术的混合模型。该模型由硅控制器和有机转导组织组成的网络组成。然后开发计算机仿真来研究模型。模拟实验证实了这样一种信念,即自然技术可以成功地用于解决特定类别的问题。该模型解决了简单但具有启发性的计算任务。所用的编程技术(进化编程)得到了详细处理。该研究的主要结论是:(1)传统的硅计算资源在模拟生物过程方面效率低下。然而,这种模拟仍然可以有利地用于解决某些问题。 (2)在某些情况下,可能会降低常规计算的刚性和高精度。在这种情况下,一定程度的不精确可能是有利的。 (3)硅和有机计算设备相互补充而不是相互替代。 (4)可以以新颖的方式使用低层次级别的大规模并行处理,这与常规的精确运算(如矩阵乘法)不同。 (5)利用自然计算技术的简单编程语言构造可以实现为常规编程语言的扩展。 (6)PN开关方法在生物芯片设计中面临的大多数主要障碍都可以通过利用自然计算技术的替代方法来规避。 (7)可以设计新颖的计算机体系结构以利用自然计算技术。 (8)在某些自适应网络应用中,线性拓扑可能比二维拓扑更好。

著录项

  • 作者

    AKINGBEHIN, KIUMI.;

  • 作者单位

    Wayne State University.;

  • 授予单位 Wayne State University.;
  • 学科 Computer Science.
  • 学位 Ph.D.
  • 年度 1986
  • 页码 224 p.
  • 总页数 224
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 自动化技术、计算机技术;
  • 关键词

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