کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4947543 | 1439583 | 2017 | 55 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A real-time FPGA implementation of a biologically inspired central pattern generator network
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله

چکیده انگلیسی
Central pattern generators (CPGs) functioning as biological neuronal circuits are responsible for generating rhythmic patterns to control locomotion. In this paper, a biologically inspired CPG composed of two reciprocally inhibitory neurons was implemented on a reconfigurable FPGA with real-time computational speed and considerably low hardware cost. High-accuracy neural circuit implementation can be computationally expensive, especially for a high-dimensional conductance-based neuron model. Thus, we aimed to present an efficient multiplier-less hardware implementation method for the investigation of real-time hardware CPG (hCPG) networks. In order to simplify the hardware implementation, a modified neuron model without nonlinear parts was given to decrease the complexity of the original model. A simple CPG network involving two chemical coupled neurons was realized which represented the pyloric dilator (PD) and lateral pyloric (LP) neurons in the crustacean pyloric CPG. The implementation results of the hCPG network showed that rhythmic behaviors were successfully reproduced and the resource consumption was dramatically reduced by using our multiplier-less implementation method. The presented FPGA-based implementation of hCPG network with remarkable performance set a prototype for the realization of other large-scale CPG networks and could be applied in bio-inspired robotics and motion rehabilitation for locomotion control.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 244, 28 June 2017, Pages 63-80
Journal: Neurocomputing - Volume 244, 28 June 2017, Pages 63-80
نویسندگان
Chen Qi, Wang Jiang, Shuangming Yang, Yingmei Qin, Bin Deng, Wei Xile,