Memristor-Based Circuit Design for Neuron With Homeostatic Plasticity

Shi, Xinming; Zeng, Zhigang; Yang, Le; Huang, Y. L.

doi:10.1109/tetci.2018.2829914

Cited by 26 publications

(11 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Numerous features of neurons such as their conduction velocity, time constants and space constants are dependent upon the combinations and densities of ion channels within the membrane [934] . In a similar fashion, artificial neuromorphic systems should be optimized (in terms of information vs energy) by mimicking this wide range of biological solutions although many basic mechanisms are still under intensive investigation [588] , [935] , [936] . For example, the TaO 2−x nanoscale filament in a Ta 2 O 5 system is determined to be crucially affected by the migration dynamics of its oxygen vacancies [937] and is has been reported to be enhanced by the introduction of an ion diffusion limiting layer at the TiN/TaO x interface [938] .…”

Section: Neural Sensorsmentioning

confidence: 99%

Functional Oxides for Photoneuromorphic Engineering: Toward a Solar Brain

Pérez‐Tomás

2019

Adv Materials Inter

View full text Add to dashboard Cite

New device concepts and new computing principles are needed to balance our ever-growing appetite for data and information with the realization of the goals of increased energy efficiency, reduction in CO 2 emissions and the circular economy. Neuromorphic or synaptic electronics is an emerging field of research aiming to overcome the current computer's Von-Neumann bottleneck by building artificial neuronal systems to mimic the extremely energy efficient biological synapses. The introduction of photovoltaic and/or photonic aspects into these neuromorphic architectures will produce self-powered adaptive electronics but may also open up new possibilities in artificial neuroscience, artificial neural communications, sensing and machine learning which would enable, in turn, a new era for computational systems owing to the possibility of attaining high bandwidths with much reduced power consumption. This perspective is focused on recent progress in the implementation of functional oxide thinfilms into photovoltaic and neuromorphic applications towards the envisioned goal of selfpowered photovoltaic neuromorphic systems or a solar brain.

show abstract

Section: Neural Sensorsmentioning

confidence: 99%

Functional Oxides for Photoneuromorphic Engineering: Toward a Solar Brain

Pérez‐Tomás

2019

Adv Materials Inter

View full text Add to dashboard Cite

show abstract

“…Therefore, it is necessary for researchers to study the circuit counterpart of pulse generators in order to adopt neuromorphic computing. For realizing pulse generation circuits in neuromorphic computing, some researchers relied on external chips to generate pulse [22,24]. However, this leads to bulk control or auxiliary circuits.…”

Section: Evolving a Memristor-based Pulse Generation Circuitmentioning

confidence: 99%

“…In this section, the proposed method will be applied to evolving a memristorbased pulse generation circuit and compared against similar purpose circuits designed manually [22,24,57,58,60].…”

Section: Evolving a Memristor-based Pulse Generation Circuitmentioning

confidence: 99%

“…In addition, we perform a case study of using the proposed approach to evolve memristor-based circuits, which are particularly relevant nowadays given the rapid development of emerging electronic devices, the wide application prospects of memristors [20] and the increasing trend of researching neuromrophic computing [21][22][23]. Considering the dynamic characteristics of memristors, there are two parts of challenges of designing memristor-based circuit manually, which are how to tune into the specific memristance by control circuits or signals, and how to manipulate the state switching behaviors of different memristors (from HRS/LRS to LRS/HRS), respectively.…”

Section: Introductionmentioning

confidence: 99%

“…As for the manual design, it is intensive and time-consuming for designers to manipulate these different characteristics of memristors during the designing process. And some devices with bulk size, such as capacitors, even external fabricated chips, are always selected to construct circuits [22,24], incurring large size and high power consumption of designed circuit system. Therefore, it is reasonable to apply the evolutionary approach to manipulate different characteristics of memristors and other devices to design memristor-based circuits pursuing the functionality, energy efficiency, and compactness synchronously.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A novel tree-based representation for evolving analog circuits and its application to memristor-based pulse generation circuit

Shi

Minku

Yao

2022

Genet Program Evolvable Mach

Self Cite

View full text Add to dashboard Cite

When applying evolutionary algorithms to circuit design automation, circuit representation is the first consideration. There have been several studies applying different circuit representations. However, they still have some problems, such as lack of design ability, which means the diversity of evolved circuits was limited by the circuit representation, and inefficient transformation from circuit representation into SPICE (Simulation Program with Integrated Circuit Emphasis) netlist. In this paper, a novel tree-based circuit representation for analog circuits is proposed, which is equipped with an intuitive and three-terminal devices friendly mapping rule between circuit representation and SPICE netlist, as well as a suitable crossover operator. Based on the proposed representation, a framework for automated analog circuit design using genetic programming is proposed to evolve both the circuit topology and device values. Three benchmark circuits are applied to evaluate the proposed approach, showing that the proposed method is feasible and evolves analog circuits with better fitness and number of components while using less fitness evaluations than existing approaches. Furthermore, considering physical scalability limits of conventional circuit elements and the increased interest in emerging technologies, a memristor-based pulse generation circuit is also evolved based on the proposed method. The feasibility of the evolved circuits is verified by circuit simulation successfully. The experiment results show that the evolved memristive circuit is more compact and has better energy efficiency compared with existing manually-designed circuits.

show abstract