Farnood Merrikh-Bayat

University of California, Santa Barbara | UCSB · Department of Electrical and Computer Engineering

Spiking neural networks, the most realistic artificial representation of biological nervous systems, are promising due to their inherent local training rules that enable low-overhead online learning, and energy-efficient information encoding. Their downside is more demanding functionality of the artificial synapses, notably including spike-timing-d...

The development of large resistive random-access memory (ReRAM) circuits depends on the availability of predictive models of their memristive cells. If progress has been made in understanding the physics of such nanodevices in the last 10 years, developing compact models, required by EDA simulation tools, that are accurate but yet fast to simulate...

The progress in the field of neural computation hinges on the use of hardware more efficient than the conventional microprocessors. Recent works have shown that mixed-signal integrated memristive circuits, especially their passive ('0T1R') variety, may increase the neuromorphic network performance dramatically, leaving far behind their digital coun...

Hardware-intrinsic security primitives employ instance-specific and process-induced variations in electronic hardware as a source of cryptographic data. Among various emerging technologies, memristors offer unique opportunities in such security applications due to their underlying stochastic operation. Here we show that the analogue tuning and nonl...

Potential advantages of analog- and mixed-signal nanoelectronic circuits, based on floating-gate devices with adjustable conductance, for neuromorphic computing had been realized long time ago. However, practical realizations of this approach suffered from using rudimentary floating-gate cells of relatively large area. Here, we report a prototype 2...

Limitations of currently dominating von Neumann architectures have pushed the research toward brain-inspired solutions like neural networks to reach new levels of computing efficiency. While these highly parallelized architectures have achieved outstanding performances at software level, their hardware implementation is still a challenging problem...

We report a monolithically integrated 3-D metal-oxide memristor crossbar circuit suitable for analog, and in particular, neuromorphic computing applications. The demonstrated crossbar is based on Pt/Al <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> O <sub xmlns:mml="http://www.w3.org/1998/Math...

The rapidly expanding hardware-intrinsic security primitives are aimed at addressing significant security challenges of a massively interconnected world in the age of information technology. The main idea of such primitives is to employ instance-specific process-induced variations in electronic hardware as a source of cryptographic data. Among the...

We have fabricated and successfully tested an analog vector-by-matrix multiplier, based on redesigned 10x12 arrays of 55 nm commercial NOR flash memory cells. The modified arrays enable high-precision individual analog tuning of each cell, with sub-1% accuracy, while keeping the highly optimized cells, with their long-term state retention, intact....

We experimentally demonstrate classification of 4x4 binary images into 4 classes, using a 3-layer mixed-signal neuromorphic network ("MLP perceptron"), based on two passive 20x20 memristive crossbar arrays, board-integrated with discrete CMOS components. The network features 10 hidden-layer and 4 output-layer analog CMOS neurons and 428 metal-oxide...

We have designed, fabricated, and successfully tested a prototype mixed-signal, 28x28-binary-input, 10-output, 3-layer neuromorphic network ("MLP perceptron"). It is based on embedded nonvolatile floating-gate cell arrays redesigned from a commercial 180-nm NOR flash memory. The arrays allow precise (~1%) individual tuning of all memory cells, havi...

We report on experimental demonstration of a mixed-signal 6-tap finite-impulse response (FIR) filter in which weights are implemented with titanium dioxide memristive devices. In the proposed design weight of a tap is stored with a relatively high precision in a memristive device that can be configured in field. Such approach enables efficient impl...

Artificial neural networks have been receiving increasing attention due to their superior performance in many information processing tasks. Typically, scaling up the size of the network results in better performance and richer functionality. However, large neural networks are challenging to implement in software and customized hardware are generall...

The purpose of this work was to demonstrate the feasibility of building recurrent artificial neural networks with hybrid complementary metal oxide semiconductor (CMOS)/memristor circuits. To do so, we modeled a Hopfield network implementing an analog-to-digital converter (ADC) with up to 8 bits of precision. Major shortcomings affecting the ADC's p...

Synapses, the most numerous elements of neural networks, are memory devices. Similarly to traditional memory applications, device density is one of the most essential metrics for large-scale artificial neural networks. This application, however, imposes a number of additional requirements, such as the continuous change of the memory state, so that...

We investigated batch and stochastic Manhattan Rule algorithms for training multilayer perceptron classifiers implemented with memristive crossbar circuits. In Manhattan Rule training, the weights are updated only using sign information of classical backpropagation algorithm. The main advantage of Manhattan Rule is its simplicity, which leads to mo...

Metal-oxide memristors have emerged as promising candidates for hardware implementation of artificial synapses - the key components of high-performance, analog neuromorphic networks - due to their excellent scaling prospects. Since some advanced cognitive tasks require spiking neuromorphic networks, which explicitly model individual neural pulses (...

Despite all the progress of semiconductor integrated circuit technology, the extreme complexity of the human cerebral cortex makes the hardware implementation of neuromorphic networks with a comparable number of devices exceptionally challenging. One of the most prospective candidates to provide comparable complexity, while operating much faster an...

We have modified a commercial NOR flash memory array to enable high-precision tuning of individual floating-gate cells for analog computing applications. The modified array area per cell in a 180 nm process is about 1.5 um^2. While this area is approximately twice the original cell size, it is still at least an order of magnitude smaller than in th...

We present a computationally inexpensive yet accurate phenomenological model of memristive behavior in titanium dioxide devices by fitting experimental data. By design, the model predicts most accurately I-V relation at small non-disturbing electrical stresses, which is often the most critical range of operation for circuit modeling. While the choi...

It is now widely accepted that memristive devices are promising candidates for the emulation of the behavior of biological synapses in neuromorphic systems. This is mainly because of the fact that like the strength of synapse, memristance of the memristive device can be tuned actively for example by the application of voltage or current. In additio...

Although fuzzy techniques promise fast meanwhile accurate modeling and control abilities for complicated systems, di?erent di?culties have been re-vealed in real situation implementations. Usually there is no escape of it-erative optimization based on crisp domain algorithms. Recently memristor structures appeared promising to implement neural netw...

In this study we will show that the variation rate of the memristance of the memristive device depends completely on its current memristance which means that it can change significantly with time during the learning phase. This phenomenon can degrade the performance of learning methods like Spike Timing-Dependent Plasticity (STDP) and cause the cor...

The paper presents experimental demonstration of 6-bit digital-to-analog (DAC) and 4-bit analog-to-digital conversion (ADC) operations implemented with a hybrid circuit consisting of Pt/TiO2-x/Pt resistive switching devices (also known as ReRAMs or memristors) and a Si operational amplifier (op-amp). In particular, a binary-weighted implementation...

In this paper, a novel neuro-fuzzy computing system is proposed where its learning is based on the creation of fuzzy relations by using a new implication method without utilizing any exact mathematical techniques. Then, a simple memristor crossbar-based analog circuit is designed to implement this neuro-fuzzy system which offers very interesting pr...

Memristor is the fourth fundamental passive circuit element with potential applications in development of analog memories, artificial brains (with the capacity of hardware training) and neuro-science. In most of these applications the memristance of the device should be set to the desired value, which is currently performed by trial and error. The...

In this paper, first we present a new explanation for the relation between logical circuits and artificial neural networks, logical circuits and fuzzy logic, and artificial neural networks and fuzzy inference systems. Then, based on these results, we propose a new neuro-fuzzy computing system which can effectively be implemented on the memristor-cr...

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 t...

Recently announcement of a physical realization of a fundamental circuit element called memristor by researchers at Hewlett Packard (HP) attracted so much interests and opened a new field in configurable or programmable electronic systems because it has properties of the perfect switch. Combination of this newly found circuit element with nanowire...

Digital documents are usually degraded during the scanning process due to the contents of the backside of the scanned manuscript. This is often caused by the show-through effect, i.e. the backside image that interferes with the main front side picture due to the intrinsic transparency of the paper. This phenomenon is one of the degradations that on...

Fuzzy inference systems always suffer from the lack of efficient structures or platforms for their hardware implementation. In this paper, we tried to overcome this problem by proposing new method for the implementation of those fuzzy inference systems which use fuzzy rule base to make inference. To achieve this goal, we have designed a multi-layer...

In May 1, 2008, researchers at Hewlett Packard (HP) announced the first physical realization of a fundamental circuit element called memristor that attracted so much interest worldwide. This newly found element can easily be combined with crossbar interconnect technology which this new structure has opened a new field in designing configurable or p...

Recently announcement of a physical realization of a fundamental circuit element called memristor by researchers at Hewlett Packard (HP) has attracted so much interest worldwide. Combination of this newly found element with crossbar interconnect technology, opened a new field in designing configurable or programmable electronic systems which can ha...

In this paper a novel neuro-fuzzy system is proposed where its learning is based on the creation of fuzzy relations by using new implication method without utilizing any exact mathematical techniques. Then, a simple memristor crossbar-based analog circuit is designed to implement this neuro-fuzzy system which offers very interesting properties. In...

Scanning process usually degrades digital documents due to the contents of the backside of the scanned manuscript. This is often because of the show-through effect, i.e. the backside image that interferes with the main front side picture mainly due to the intrinsic transparency of the paper used for printing or writing. In this paper, we first use...

In May 1, 2008, researchers at Hewlett Packard (HP) announced the first physical realization of a fundamental circuit element called memristor that attracted so much interest worldwide. This newly found element can easily be combined with crossbar interconnect technology which this new structure has opened a new field in designing configurable or p...

It is now widely accepted that memristive devices are perfect candidates for the emulation of biological synapses in neuromorphic systems. This is mainly because of the fact that like the strength of synapse, memristance of the memristive device can be tuned actively (e.g., by the application of volt- age or current). In addition, it is also possib...

In almost all of the currently working circuits, especially in analog circuits implementing signal processing applications, basic arithmetic operations such as multiplication, addition, subtraction and division are performed on values which are represented by voltages or currents. However, in this paper, we propose a new and simple method for perfo...

This paper deals with the problem of designing the PI ^λ D ^μ-type controllers for minimum-phase fractional systems of rational order. In such systems, the powers of the Laplace variable, s , are limited to rational numbers. Unlike many existing methods that use numerical optimisation algorithms, the proposed method is based on...

This paper deals with the boundary control problem for a certain class of linear infinite-dimensional systems commonly known as fractional-delay systems. It is assumed that the systems under consideration are, in general, described by multi-valued transfer functions. In this paper, we restrict our studies to a class of multi-valued transfer functio...

Digital documents are usually degraded during the scanning process due to the printings existing on the backside of the scanning manuscript. This is often caused by the so called show-through effect, the image that interferes with the main picture due to the intrinsic opacity of the paper. This phenomenon is on type of degradation that one would li...