Modeling of Coupled Memristive-Based Architectures Applicable to Neural Network Models

This chapter explores the dynamic behavior of dual flux coupled memristor circuits in order to explore the uncharted territory of the fundamental theory of memristor circuits. Neuromorphic computing anticipates highly dense systems of memristive networks, and with nanoscale devices within such close proximity to one another, it is anticipated that flux and charge coupling between adjacent memristors will have a bearing upon their operation. Using the constitutive relations of memristors, various cases of flux coupling are mathematically modeled. This involves analyzing two memristors connected in composite, both serially and in parallel in various polarity configurations. The new behavior of two coupled memristors is characterized based on memristive state equations, and memductance variation represented in terms of voltage, current, charge and flux. The rigorous mathematical analysis based on the fundamental circuit equations of ideal memristors affirms the memristor closure theorem, where coupled memristor circuits behave as different types of memristors with higher complexity

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Thesis (M.Eng.Sc.)--University of Adelaide, Dept. of Electrical Engineering, 197

Memristor MOS Content Addressable Memory (MCAM): Hybrid Architecture for Future High Performance Search Engines

Large-capacity Content Addressable Memory (CAM) is a key element in a wide variety of applications. The inevitable complexities of scaling MOS transistors introduce a major challenge in the realization of such systems. Convergence of disparate technologies, which are compatible with CMOS processing, may allow extension of Moore's Law for a few more years. This paper provides a new approach towards the design and modeling of Memristor (Memory resistor) based Content Addressable Memory (MCAM) using a combination of memristor MOS devices to form the core of a memory/compare logic cell that forms the building block of the CAM architecture. The non-volatile characteristic and the nanoscale geometry together with compatibility of the memristor with CMOS processing technology increases the packing density, provides for new approaches towards power management through disabling CAM blocks without loss of stored data, reduces power dissipation, and has scope for speed improvement as the technology matures.Comment: 10 pages, 11 figure

Memristor-based Synaptic Networks and Logical Operations Using In-Situ Computing

We present new computational building blocks based on memristive devices. These blocks, can be used to implement either supervised or unsupervised learning modules. This is achieved using a crosspoint architecture which is an efficient array implementation for nanoscale two-terminal memristive devices. Based on these blocks and an experimentally verified SPICE macromodel for the memristor, we demonstrate that firstly, the Spike-Timing-Dependent Plasticity (STDP) can be implemented by a single memristor device and secondly, a memristor-based competitive Hebbian learning through STDP using a $1\times 1000$ synaptic network. This is achieved by adjusting the memristor's conductance values (weights) as a function of the timing difference between presynaptic and postsynaptic spikes. These implementations have a number of shortcomings due to the memristor's characteristics such as memory decay, highly nonlinear switching behaviour as a function of applied voltage/current, and functional uniformity. These shortcomings can be addressed by utilising a mixed gates that can be used in conjunction with the analogue behaviour for biomimetic computation. The digital implementations in this paper use in-situ computational capability of the memristor.Comment: 18 pages, 7 figures, 2 table

An Analytical Approach for Memristive Nanoarchitectures

As conventional memory technologies are challenged by their technological physical limits, emerging technologies driven by novel materials are becoming an attractive option for future memory architectures. Among these technologies, Resistive Memories (ReRAM) created new possibilities because of their nano-features and unique $I$-$V$ characteristics. One particular problem that limits the maximum array size is interference from neighboring cells due to sneak-path currents. A possible device level solution to address this issue is to implement a memory array using complementary resistive switches (CRS). Although the storage mechanism for a CRS is fundamentally different from what has been reported for memristors (low and high resistances), a CRS is simply formed by two series bipolar memristors with opposing polarities. In this paper our intention is to introduce modeling principles that have been previously verified through measurements and extend the simulation principles based on memristors to CRS devices and hence provide an analytical approach to the design of a CRS array. The presented approach creates the necessary design methodology platform that will assist designers in implementation of CRS devices in future systems.Comment: 12 pages, 10 figures, 4 table

Image capture using integrated 3D SoftChip technology

Mobile multimedia communication has rapidly become a significant area of research and development. The processing requirements for the capture, conversion, compression, decompression, enhancement, display, etc. of high quality multimedia content places heavy demands even on current ULSI (ultra large scale integration) systems, particularly for mobile applications where area and power are primary considerations. The system presented is designed as a vertically integrated (3D) system comprising two distinct layers bonded together using indium bump technology. The top layer is a CMOS imaging array containing analog-to-digital converters, and a buffer memory. The bottom layer takes the form of a configurable array processor (CAP), a highly parallel array of soft programmable processors capable of carrying out complex processing tasks directly on data stored in the top plane. Until recently, the dominant format of data in imaging devices has been analog. The analog photocurrent or sampled voltage is transferred to the ADC via a column or a column/row bus. In the proposed system, an array of analog-to-digital converters is distributed, so that a one-bit cell is associated with one sensor. The analog-to-digital converters are algorithmic current-mode converters. Eight such cells are cascaded to form an 8-bit converter. Additionally, each photosensor is equipped with a current memory cell, and multiple conversions are performed with scaled values of the photocurrent for colour processing

Prognostic factors of survival time after hematopoietic stem cell transplant in acute lymphoblastic leukemia patients: Cox proportional hazard versus accelerated failure time models

<p>Abstract</p> <p>Background</p> <p>The aim of this study is to evaluate the prognostic factors of overall survival (OS) after haematopoietic stem cell transplant (HSCT) in acute lymphoblastic leukaemia (ALL) patients using accelerated failure time (AFT), Cox proportional hazard (PH), and Cox time-varying coefficient models.</p> <p>Methods</p> <p>206 patients were enrolled after HSCH in Shariati Hospital between 1993 and 2007. There was evidence of marked departures from the proportional hazards assumption with two prognostic factors, relapse and chronic graft-versus-host disease (cGVHD) (P < .001). Performance among AFT and Cox's models was assessed using explained variation and goodness of fit methods. Discrimination among the exponential, Weibull, generalized gamma (GG), log-logistic, and lognormal distributions was done using maximum likelihood and Akaike information criteria.</p> <p>Results</p> <p>The 5-year OS was 52% (95%CI: 47.3–56.7). Peak mortality hazard occurred at months 6–7 after HSCT followed by a decreasing trend. In univariate analysis, the data was better fitted by GG distribution than by other distributions. Univariate analysis using GG distribution showed a positive association between OS with acute graft-versus-host disease (aGVHD) (P = .021), no relapse (P < .001), cGVHD (P < .001), neutrophil recovery (P < .001) and platelet recovery (P < .001). Based on Cox PH models; however cGVHD and relapse were the predictive factors of OS (P < .001). Multivariate analysis indicated that, OS is related to relapse (P < .001) and platelet recovery (P = .037), where predictive power of Weibull AFT models was superior to Cox PH model and Cox with time-varying coefficient (R²= 0.46 for AFT, R²= .21 for Cox PH and R²= .34 for Cox time-varying coefficient). Cox-Snell residual shows Weibull AFT fitted to data better than other distributions in multivariate analysis.</p> <p>Conclusion</p> <p>We concluded that AFT distributions can be a useful tool for recognizing prognostic factors of OS in acute lymphoblastic leukemia patients.</p

Effect of 670 Nm Laser Beam on the Action Potentials of Sural Nerve in Healthy Individuals

Introduction: Low Level Laser (LLL) is being used in physiotherapy for pain relief in various pathologies and particularly on peripheral nerve entrapments. In the present study, the effect of LLL on the electrophysiological parameters of sural in humans was investigated. The results might be used as a basis for further clinical research in abnormal conditions. Methods and Materials: Thirty-eight normal men voluntarily participated in the current study and 670 nm LLL beam was applied to the left sural nerve at 5 points for 10 sessions. The electrophysiological parameters such as onset latency, peak latency, negative peak amplitude, peak to peak amplitude, and duration were measured before and after the application of LLL (0.5, 1.5 &amp; 2.5 J/cm² energy density). Results: Overall, 670 nm laser beam increased the latency and reduced the nerve conduction velocity (NCV). In addition, LLL beam decreased the amplitude of action potentials. Among the various values of energy densities, application of 2.5 J/cm² had the most effective results (P &lt; 0.001). Conclusion: These results might suggest that 670 nm laser beam could affect the latency and reduce the NCV in sural nerve of human. Probably, LLL affects the bioelectric and bioenergetic properties of the neural biomembrane. These findings might have clinical signlificance in non-surgical treatment of entrapment syndromes, such as carpal, tarsal syndromes and trigeminal entrapment in human. Further investigations are needed to elucidate the effects of LLL beam on the human peripheral nerves in pathological conditions.Keywords: Low-level laser, Sural nerve, Electrophysiology, Pai