Memristive model of amoeba learning
نویسندگان
چکیده
منابع مشابه
Memristive model of amoeba learning.
Recently, it was shown that the amoebalike cell Physarum polycephalum when exposed to a pattern of periodic environmental changes learns and adapts its behavior in anticipation of the next stimulus to come. Here we show that such behavior can be mapped into the response of a simple electronic circuit consisting of a LC contour and a memory-resistor (a memristor) to a train of voltage pulses tha...
متن کاملMemristive model of amoeba's learning
Recently, behavioural intelligence of the plasmodia of the true slime mold has been demonstrated. It was shown that a large amoeba-like cell Physarum polycephalum subject to a pattern of periodic environmental changes learns and changes its behaviour in anticipation of the next stimulus to come. Currently, it is not known what specific mechanisms are responsible for such behaviour. Here, we sho...
متن کاملHardware neuromorphic learning systems utilizing memristive devices
Hardware Neuromorphic Learning Systems Utilizing Memristive Devices
متن کاملComplex Learning in Bio-plausible Memristive Networks
The emerging memristor-based neuromorphic engineering promises an efficient computing paradigm. However, the lack of both internal dynamics in the previous feedforward memristive networks and efficient learning algorithms in recurrent networks, fundamentally limits the learning ability of existing systems. In this work, we propose a framework to support complex learning functions by introducing...
متن کاملSPICE model of memristive devices with threshold
Although memristive devices with threshold voltages are the norm rather than the exception in experimentally realizable systems, their SPICE programming is not yet common. Here, we show how to implement such systems in the SPICE environment. Specifically, we present SPICE models of a popular voltage-controlled memristive system specified by five different parameters for PSPICE and NGSPICE circu...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Physical Review E
سال: 2009
ISSN: 1539-3755,1550-2376
DOI: 10.1103/physreve.80.021926