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Art of electronics

Neuromorphic computing has come to refer to a variety of brain-inspired computers, devices, and models that contrast the pervasive von Neumann computer architecture This biologically inspired approach has created highly connected synthetic neurons and synapses that can be used to model neuroscience theories as well as solve challenging machine learning problems The promise of the technology is to create a brain-like ability to learn and adapt, but the technical challenges are significant, starting with an accurate neuroscience model of how the brain works, to finding materials and engineering breakthroughs to build devices to support these models, to creating a programming framework so the systems can learn, to creating applications with brain-like capabilities In this work, we provide a comprehensive survey of the research and motivations for neuromorphic computing over its history We begin with a 35-year review of the motivations and drivers of neuromorphic computing, then look at the major research areas of the field, which we define as neuro-inspired models, algorithms and learning approaches, hardware and devices, supporting systems, and finally applications We conclude with a broad discussion on the major research topics that need to be addressed in the coming years to see the promise of neuromorphic computing fulfilled The goals of this work are to provide an exhaustive review of the research conducted in neuromorphic computing since the inception of the term, and to motivate further work by illuminating gaps in the field where new research is needed

A Survey of Neuromorphic Computing and Neural Networks in Hardware.

The rapid development of information technology has led to urgent requirements for high efficiency and ultralow power consumption. In the past few decades, neuromorphic computing has drawn extensive attention due to its promising capability in processing massive data with extremely low power consumption. Here, we offer a comprehensive review on emerging artificial neuromorphic devices and their applications. In light of the inner physical processes, we classify the devices into nine major categories and discuss their respective strengths and weaknesses. We will show that anion/cation migration-based memristive devices, phase change, and spintronic synapses have been quite mature and possess excellent stability as a memory device, yet they still suffer from challenges in weight updating linearity and symmetry. Meanwhile, the recently developed electrolyte-gated synaptic transistors have demonstrated outstanding energy efficiency, linearity, and symmetry, but their stability and scalability still need to be optimized. Other emerging synaptic structures, such as ferroelectric, metal–insulator transition based, photonic, and purely electronic devices also have limitations in some aspects, therefore leading to the need for further developing high-performance synaptic devices. Additional efforts are also demanded to enhance the functionality of artificial neurons while maintaining a relatively low cost in area and power, and it will be of significance to explore the intrinsic neuronal stochasticity in computing and optimize their driving capability, etc. Finally, by looking into the correlations between the operation mechanisms, material systems, device structures, and performance, we provide clues to future material selections, device designs, and integrations for artificial synapses and neurons.

A comprehensive review on emerging artificial neuromorphic devices

Transformer Hydrogels: A Review

Neuromorphic computation is one of the axes of parallel distributed processing, and memristor-based synaptic weight is considered as a key component of this type of computation. However, the material properties of memristors, including material related physics, are not yet matured. In parallel with memristors, CMOS based Graphics Processing Unit, Field Programmable Gate Array, and Application Specific Integrated Circuit are also being developed as dedicated artificial intelligence (AI) chips for fast computation. Therefore, it is necessary to analyze the competitiveness of the memristor-based neuromorphic device in order to position the memristor in the appropriate position of the future AI ecosystem. In this article, the status of memristor-based neuromorphic computation was analyzed on the basis of papers and patents to identify the competitiveness of the memristor properties by reviewing industrial trends and academic pursuits. In addition, material issues and challenges are discussed for implementing the memristor-based neural processor.

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Perspective: A review on memristive hardware for neuromorphic computation

A spiking and bursting neuron circuit based on memristor

Actively simulated grounded inductors have been used in several applications ranging from filter to oscillator design as well as cancelation of parasitic inductances. In this paper, new lossless grounded inductance simulator employing only one voltage differencing buffer amplifier (VDBA) and two passive components is proposed. The aim of this paper is to present new inductance simulator using the minimum number of active and passive components. The proposed inductance simulator can be tuned electronically by changing the transconductance of the VDBA. Finally, using the proposed inductance simulator a band-pass filter is constructed. The performance of the filter is simulated by using PSPICE and simulation results are verified experimentally.

Lossless grounded inductance simulator employing single VDBA and its experimental band-pass filter application

Dielectric characterization and electroresponsive behavior of glutaraldehyde (GA) crosslinked sodium alginate/poly(acrylic acid) (SA-AA-GA) interpenetrating polymer network (IPN) films were studied. Further characterizations of the films were performed by Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), differential scanning calorimetry (DSC), and swelling measurements. Sodium alginate (SA) and SA-AA semi-IPN films were also prepared for comparison. The effect of initial concentration of acrylic acid on the dielectric and thermal properties of SA-AA semi-IPN and SA-AA-GA full-IPN films was studied. The presence of poly(acrylic acid) and the crosslinking of SA by GA decreased the dielectric constant and the conductivity values. The bending of SA-AA-GA films in an electrolyte solution at 8 V was investigated as a function of electrolyte (NaCl) concentration (0.05–0.15 M) and the composition of the film. The response rate of SA-AA-GA films to electric field decreased with the increase in PAA content of the film. Amongst the NaCl solutions with various concentrations, the maximum total bending of SA-AA-GA film was obtained in 0.15 M NaCl solution.

Synthesis, characterization and bending behavior of electroresponsive sodium alginate/poly(acrylic acid) interpenetrating network films under an electric field stimulus

In this study, Ca 21 -crosslinked sodium alginate (SA) gel films (SA-Ca/SA2-Ca) have been prepared, and their structural and thermal characterizations were investigated using fourier transform infrared spectroscopy, Xray diffraction, differential scanning calorimetry, and thermogravimetric analysis, respectively. Dielectric characterization was performed at room temperature in the frequency range of 12 Hz–100 kHz. The equilibrium swelling value (ESV) of gel films was determined both in distilled water and in 0.1 M sodium chloride (NaCl) solution at room temperature. Sodium alginate films (SA/ SA2) were also prepared for use as reference. The effect of the crosslinking of sodium alginate on the dielectric and thermal properties of gel films was investigated by comparing the properties of gel films with those of SA/ SA2 films. Although ESV of Ca 21 -crosslinked SA film in distilled water is about 350 gH2O/gpolymer, it decreased into one third in 0.1 M NaCl solution. The crosslinking of SA did not significantly affect the thermal properties, but it decreased the b-relaxation associated with the polar side groups. Frequency spectra of electric modulus, impedance and Cole-Cole plots confirmed the higher conductance values of SA-Ca films at low frequencies than those of SA film due to the presence of by-product of crosslinking. POLYM. ENG. SCI., 54:1372– 1382, 2014. V C 2013 Society of Plastics Engineers

Dielectric, thermal, and swelling properties of calcium ion-crosslinked sodium alginate film

In the present paper, configurations of the three new voltage-mode universal biquad filters are presented. The first filter is three-inputs single-output (TISO) filter which can realize all the five standard types of biquadratic functions in voltage-mode that is low-pass, band-pass, high-pass, band-stop and all-pass filter with single VDCC. The second filter has single-input and dual-output, which can also simultaneously realize the high-pass and band-pass filter functions. The third circuit is universal filter with single-input and dual-output, which can simultaneously realize low-pass and band-pass filters. Simulation results are given to confirm the theoretical analysis. The presented biquad filters are simulated using TSMC CMOS 0.18 µm technology. To realize TISO filter with discrete elements VDCC block experimentally generated with operational transconductance amplifier, OPA860. Experimental results of the filter agreed well with the theoretical analysis and SPICE simulations.

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Koray Gürkan

Papers

A spiking and bursting neuron circuit based on memristor

Lossless grounded inductance simulator employing single VDBA and its experimental band-pass filter application

Synthesis, characterization and bending behavior of electroresponsive sodium alginate/poly(acrylic acid) interpenetrating network films under an electric field stimulus

Dielectric, thermal, and swelling properties of calcium ion-crosslinked sodium alginate film

Design and experiment of VDCC-based voltage mode universal filter