1,505 research outputs found
Nonlinear Switched-Capacitor Networks: Basic Principles and Piecewise-Linear Design
The applicability of switched-capacitor (SC) components to the design of nonlinear networks is extensively discussed in this paper. The main objective is to show that SC's can be efficiently used for designing nonlinear networks. Moreover, the design methods to be proposed here are fully compatible with general synthesis methods for nonlinear n -ports. Different circuit alternatives are given and their potentials are evaluated.Office of Naval Research (USA) N00014-76-C-0572Comisión Interministerial de Ciencia y Tecnología 0235/81Semiconductor Research Corporation (USA) 82-11-00
Teaching Memory Circuit Elements via Experiment-Based Learning
The class of memory circuit elements which comprises memristive,
memcapacitive, and meminductive systems, is gaining considerable attention in a
broad range of disciplines. This is due to the enormous flexibility these
elements provide in solving diverse problems in analog/neuromorphic and
digital/quantum computation; the possibility to use them in an integrated
computing-memory paradigm, massively-parallel solution of different
optimization problems, learning, neural networks, etc. The time is therefore
ripe to introduce these elements to the next generation of physicists and
engineers with appropriate teaching tools that can be easily implemented in
undergraduate teaching laboratories. In this paper, we suggest the use of
easy-to-build emulators to provide a hands-on experience for the students to
learn the fundamental properties and realize several applications of these
memelements. We provide explicit examples of problems that could be tackled
with these emulators that range in difficulty from the demonstration of the
basic properties of memristive, memcapacitive, and meminductive systems to
logic/computation and cross-bar memory. The emulators can be built from
off-the-shelf components, with a total cost of a few tens of dollars, thus
providing a relatively inexpensive platform for the implementation of these
exercises in the classroom. We anticipate that this experiment-based learning
can be easily adopted and expanded by the instructors with many more case
studies.Comment: IEEE Circuits and Systems Magazine (in press
Generalized Parity-Time Symmetry Condition for Enhanced Sensor Telemetry
Wireless sensors based on micro-machined tunable resonators are important in
a variety of applications, ranging from medical diagnosis to industrial and
environmental monitoring.The sensitivity of these devices is, however, often
limited by their low quality (Q) factor.Here, we introduce the concept of
isospectral party time reciprocal scaling (PTX) symmetry and show that it can
be used to build a new family of radiofrequency wireless microsensors
exhibiting ultrasensitive responses and ultrahigh resolution, which are well
beyond the limitations of conventional passive sensors. We show theoretically,
and demonstrate experimentally using microelectromechanical based wireless
pressure sensors, that PTXsymmetric electronic systems share the same
eigenfrequencies as their parity time (PT)-symmetric counterparts, but
crucially have different circuit profiles and eigenmodes. This simplifies the
electronic circuit design and enables further enhancements to the extrinsic Q
factor of the sensors
On Spike-Timing-Dependent-Plasticity, Memristive Devices, and Building a Self-Learning Visual Cortex
In this paper we present a very exciting overlap between emergent nanotechnology and neuroscience, which has been discovered by neuromorphic engineers. Specifically, we are linking one type of memristor nanotechnology devices to the biological synaptic update rule known as spike-time-dependent-plasticity (STDP) found in real biological synapses. Understanding this link allows neuromorphic engineers to develop circuit architectures that use this type of memristors to artificially emulate parts of the visual cortex. We focus on the type of memristors referred to as voltage or flux driven memristors and focus our discussions on a behavioral macro-model for such devices. The implementations result in fully asynchronous architectures with neurons sending their action potentials not only forward but also backward. One critical aspect is to use neurons that generate spikes of specific shapes. We will see how by changing the shapes of the neuron action potential spikes we can tune and manipulate the STDP learning rules for both excitatory and inhibitory synapses. We will see how neurons and memristors can be interconnected to achieve large scale spiking learning systems, that follow a type of multiplicative STDP learning rule. We will briefly extend the architectures to use three-terminal transistors with similar memristive behavior. We will illustrate how a V1 visual cortex layer can assembled and how it is capable of learning to extract orientations from visual data coming from a real artificial CMOS spiking retina observing real life scenes. Finally, we will discuss limitations of currently available memristors. The results presented are based on behavioral simulations and do not take into account non-idealities of devices and interconnects. The aim of this paper is to present, in a tutorial manner, an initial framework for the possible development of fully asynchronous STDP learning neuromorphic architectures exploiting two or three-terminal memristive type devices. All files used for the simulations are made available through the journal web site1
Threshold Switching and Self-Oscillation in Niobium Oxide
Volatile threshold switching, or current controlled negative
differential resistance (CC-NDR), has been observed in a range of
transition metal oxides. Threshold switching devices exhibit a
large non-linear change in electrical conductivity, switching
from an insulating to a metallic state under external stimuli.
Compact, scalable and low power threshold switching devices are
of significant interest for use in existing and emerging
technologies, including as a selector element in high-density
memory arrays and as solid-state oscillators for hardware-based
neuromorphic computing.
This thesis explores the threshold switching in amorphous NbOx
and the properties of individual and coupled oscillators based on
this response. The study begins with an investigation of
threshold switching in Pt/NbOx/TiN devices as a function device
area, NbOx film thickness and temperature, which provides
important insight into the structure of the self-assembled
switching region. The devices exhibit combined threshold-memory
behaviour after an initial voltage-controlled forming
process, but exhibit symmetric threshold switching when the RESET
and SET currents are kept below a critical value. In this mode,
the threshold and hold voltages are shown to be independent of
the device area and film thickness, and the threshold power,
while independent of device area, is shown to decrease with
increasing film thickness. These results are shown to be
consistent with a structure in which the threshold switching
volume is confined, both laterally and vertically, to the region
between the residual memory filament and the electrode, and where
the memory filament has a core-shell structure comprising a
metallic core and a semiconducting shell. The veracity of this
structure is demonstrated by comparing experimental results with
the predictions of a resistor network model, and detailed finite
element simulations.
The next study focuses on electrical self-oscillation of an NbOx
threshold switching device incorporated into a Pearson-Anson
circuit configuration. Measurements confirm stable operation of
the oscillator at source voltages as low as 1.06 V, and
demonstrate frequency control in the range from 2.5 to 20.5 MHz
with maximum frequency tuning range of 18 MHz/V. The oscillator
exhibit three distinct oscillation regimes: sporadic spiking,
stable oscillation and damped oscillation. The oscillation
frequency, peak-to-peak amplitude and frequency are shown to be
temperature and voltage dependent with stable oscillation
achieved for temperatures up to ∼380 K. A physics-based
threshold switching model with inclusion of device and circuit
parameters is shown to explain the oscillation waveform and
characteristic.
The final study explores the oscillation dynamics of capacitively
coupled Nb/Nb2O5 relaxation oscillators. The coupled system
exhibits rich collective behaviour, from weak coupling to
synchronisation, depending on the negative differential
resistance response of the individual devices, the operating
voltage and the coupling capacitance. These coupled oscillators
are shown to exhibit stable frequency and phase locking states at
source voltages as low as 2.2 V with MHz frequency tunable range.
The numerical simulation of the coupled system highlights the
role of source voltage, and circuit and device capacitance in
controlling the coupling modes and dynamics
Nonlinear Load Compensation
Nonlinear loads pose significant problems to power engineers, and have proliferated in occurrence over the past few decades. This project seeks to design and simulate a process by which one might mitigate the harmful consequences that result from their usage, employing signals processing techniques, logical decision-making processes, and currently available power electronics hardware
- …