Memristor Crossbar-Based Hardware Implementation of the IDS Method

@article{MerrikhBayat2011MemristorCH,
  title={Memristor Crossbar-Based Hardware Implementation of the IDS Method},
  author={F. Merrikh-Bayat and S. B. Shouraki and Ali Rohani},
  journal={IEEE Transactions on Fuzzy Systems},
  year={2011},
  volume={19},
  pages={1083-1096}
}
Ink drop spread (IDS) is the engine of an active learning method, which is the methodology of soft computing. IDS, as a pattern-based processing unit, extracts useful information from a system that is subjected to modeling. In spite of its excellent potential to solve problems such as classification and modeling compared with other soft-computing tools, finding its simple and fast hardware implementation is still a challenge. This paper describes a new hardware implementation of the IDS method… Expand
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References

SHOWING 1-10 OF 33 REFERENCES
Mixed analog-digital crossbar-based hardware implementation of sign–sign LMS adaptive filter
TLDR
This paper will propose a new mixed analog-digital circuit as a hardware implementation of the sign–sign least mean square (LMS) adaptive filter algorithm, based on the simple memristor crossbar structure. Expand
Performance of the IDS Method as a Soft Computing Tool
TLDR
This study demonstrates that the IDS method has superior capability to function as a soft computing tool based on comparative evaluations with artificial neural networks and fuzzy inference systems. Expand
Memristor-The missing circuit element
A new two-terminal circuit element-called the memristorcharacterized by a relationship between the charge q(t)\equiv \int_{-\infty}^{t} i(\tau) d \tau and the flux-linkage \varphi(t)\equiv \int_{-Expand
A high performance IDS processing unit for a new fuzzy-based modeling
TLDR
A developed high performance IDS processing unit enables ALM-based modeling systems to increase real-time capabilities and a consideration of the redundancy of IDSprocessing units is described. Expand
SPICE modeling of memristive, memcapacitative and meminductive systems
TLDR
It is shown that the memristor, designed in HP laboratories, can be modeled as a first-order memristive system with nonlinear dependence of the time derivative of the state variable on this variable and on the current flowing through. Expand
A novel hardware implementation of IDS method
TLDR
A new implementation of a hardware unit implementing the ink drop spread (IDS) method is presented, which uses a fuzzy curve fitting technique for behavior extraction or finding the input-output transformation of each of the single-input single-output systems. Expand
The missing memristor found
TLDR
It is shown, using a simple analytical example, that memristance arises naturally in nanoscale systems in which solid-state electronic and ionic transport are coupled under an external bias voltage. Expand
Memristive model of amoeba’s learning
TLDR
It is shown that memristive behaviour can be mapped into the response of a simple electronic circuit consisting of an LC contour and a memory-resistor (a memristor) to a train of voltage pulses that mimic environment changes. Expand
A study on the modeling ability of the IDS method: A soft computing technique using pattern-based information processing
TLDR
Experimental results demonstrated that the IDS method can handle various modeling targets, ranging from logic operations to complex nonlinear systems, and that its modeling performance is satisfactory in comparison with that of feedforward neural networks. Expand
Proposal for Memristors in Signal Processing
  • B. Mouttet
  • Engineering, Computer Science
  • NanoNet
  • 2008
TLDR
It is proposed to combine such memristors with operational amplifier circuitry and fixed resistor elements so as to form a programmable signal processor capable of selective transmission and multiplexing of multiple signals for applications in communications and programmable drive waveform control. Expand
...
1
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3
4
...