کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
406690 678105 2014 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Analog feedback in Euglena-based neural network computing – Enhancing solution-search capability through reaction threshold diversity among cells
ترجمه فارسی عنوان
بازخورد آنالوگ در شبکه عصبی مبتنی بر یوگلنا محاسبه یک ؟؟ افزایش توانایی جستجو در راه حل ها از طریق تنش آستانه واکنش در میان سلول ها
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی

Microbe-based neural network computing, where the reaction of microbial cells to external stimuli is incorporated in the function of virtual neurons, has high potential for developing soft computing based on the survival strategies of the microbe. To utilize reaction-threshold diversity among the cells, we examined analog feedback in Euglena-based neurocomputing by solving a simple combinatorial optimization problem. The analog feedback was performed by blue light illumination to Euglena cells, where the intensity of the blue light was controlled using the Hopfield-Tank algorithm with a sigmoid function. The solution patterns obtained with analog feedback had greater variations than those with digital feedback, implying that the solution-search capability of Euglena-based neurocomputing is enhanced by analog feedback. Moreover, the solutions obtained with analog feedback comprised one stable core-motive selection and additional flexible selections, which are associated with hesitation shown by humans when faced with a frustrated task. The study shows that using analog feedback in Euglena-based neurocomputing is promising in terms of incorporating the diversity of photoreactions of Euglena cells to enhance the solution-search capability for combinatorial optimization problems and to utilize the adaptive reaction of Euglena cells.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 140, 22 September 2014, Pages 291–298
نویسندگان
, , , , ,