8 research outputs found
Synaptic rewiring in neuromorphic VLSI for topographic map formation
A generalised model of biological topographic map development is presented which combines
both weight plasticity and the formation and elimination of synapses (synaptic rewiring)
as well as both activity-dependent and -independent processes. The question of whether an
activity-dependent process can refine a mapping created by an activity-independent process
is investigated using a statistical approach to analysingmapping quality. The model is
then implemented in custom mixed-signal VLSI. Novel aspects of this implementation include:
(1) a distributed and locally reprogrammable address-event receiver, with which
large axonal fan-out does not reduce channel capacity; (2) an analogue current-mode
circuit for Euclidean distance calculation which is suitable for operation across multiple
chips; (3) slow probabilistic synaptic rewiring driven by (pseudo-)random noise; (4) the
application of a very-low-current design technique to improving the stability of weights
stored on capacitors; (5) exploiting transistor non-ideality to implement partially weightdependent
spike-timing-dependent plasticity; (6) the use of the non-linear capacitance of
MOSCAP devices to compensate for other non-linearities. The performance of the chip
is characterised and it is shown that the fabricated chips are capable of implementing the
model, resulting in biologically relevant behaviours such as activity-dependent reduction
of the spatial variance of receptive fields. Complementing a fast synaptic weight change
mechanism with a slow synapse rewiring mechanism is suggested as a method of increasing
the stability of learned patterns
Adaptive extreme edge computing for wearable devices
Wearable devices are a fast-growing technology with impact on personal healthcare for both society and economy. Due to the widespread of sensors in pervasive and distributed networks, power consumption, processing speed, and system adaptation are vital in future smart wearable devices. The visioning and forecasting of how to bring computation to the edge in smart sensors have already begun, with an aspiration to provide adaptive extreme edge computing. Here, we provide a holistic view of hardware and theoretical solutions towards smart wearable devices that can provide guidance to research in this pervasive computing era. We propose various solutions for biologically plausible models for continual learning in neuromorphic computing technologies for wearable sensors. To envision this concept, we provide a systematic outline in which prospective low power and low latency scenarios of wearable sensors in neuromorphic platforms are expected. We successively describe vital potential landscapes of neuromorphic processors exploiting complementary metal-oxide semiconductors (CMOS) and emerging memory technologies (e.g. memristive devices). Furthermore, we evaluate the requirements for edge computing within wearable devices in terms of footprint, power consumption, latency, and data size. We additionally investigate the challenges beyond neuromorphic computing hardware, algorithms and devices that could impede enhancement of adaptive edge computing in smart wearable devices
Chemical Bionics - a novel design approach using ion sensitive field effect transistors
In the late 1980s Carver Mead introduced Neuromorphic engineering in which various
aspects of the neural systems of the body were modelled using VLSI1 circuits. As a result most bio-inspired systems to date concentrate on modelling the electrical behaviour of neural systems such as the eyes, ears and brain. The reality is however that biological systems rely on chemical as well as electrical principles in order to function.
This thesis introduces chemical bionics in which the chemically-dependent physiology
of specific cells in the body is implemented for the development of novel bio-inspired therapeutic devices. The glucose dependent pancreatic beta cell is shown to be one such cell, that is designed and fabricated to form the first silicon metabolic cell. By replicating the bursting behaviour of biological beta cells, which respond to changes in blood glucose, a bio-inspired prosthetic for glucose homeostasis of Type I diabetes is demonstrated.
To compliment this, research to further develop the Ion Sensitive Field Effect Transistor (ISFET) on unmodified CMOS is also presented for use as a monolithic sensor for chemical bionic systems. Problems arising by using the native passivation of CMOS as a sensing surface are described and methods of compensation are presented. A model for the operation of the device in weak inversion is also proposed for exploitation of its physical primitives
to make novel monolithic solutions. Functional implementations in various technologies is also detailed to allow future implementations chemical bionic circuits.
Finally the ISFET integrate and fire neuron, which is the first of its kind, is presented to be used as a chemical based building block for many existing neuromorphic circuits. As an example of this a chemical imager is described for spatio-temporal monitoring of chemical species and an acid base discriminator for monitoring changes in concentration around a fixed threshold is also proposed
Resistive switching in ALD metal-oxides with engineered interfaces
L'abstract è presente nell'allegato / the abstract is in the attachmen
Low Power Memory/Memristor Devices and Systems
This reprint focusses on achieving low-power computation using memristive devices. The topic was designed as a convenient reference point: it contains a mix of techniques starting from the fundamental manufacturing of memristive devices all the way to applications such as physically unclonable functions, and also covers perspectives on, e.g., in-memory computing, which is inextricably linked with emerging memory devices such as memristors. Finally, the reprint contains a few articles representing how other communities (from typical CMOS design to photonics) are fighting on their own fronts in the quest towards low-power computation, as a comparison with the memristor literature. We hope that readers will enjoy discovering the articles within
Silicon Nanodevices
This book is a collection of scientific articles which brings research in Si nanodevices, device processing, and materials. The content is oriented to optoelectronics with a core in electronics and photonics. The issue of current technology developments in the nanodevices towards 3D integration and an emerging of the electronics and photonics as an ultimate goal in nanotechnology in the future is presented. The book contains a few review articles to update the knowledge in Si-based devices and followed by processing of advanced nano-scale transistors. Furthermore, material growth and manufacturing of several types of devices are presented. The subjects are carefully chosen to critically cover the scientific issues for scientists and doctoral students
MOCAST 2021
The 10th International Conference on Modern Circuit and System Technologies on Electronics and Communications (MOCAST 2021) will take place in Thessaloniki, Greece, from July 5th to July 7th, 2021. The MOCAST technical program includes all aspects of circuit and system technologies, from modeling to design, verification, implementation, and application. This Special Issue presents extended versions of top-ranking papers in the conference. The topics of MOCAST include:Analog/RF and mixed signal circuits;Digital circuits and systems design;Nonlinear circuits and systems;Device and circuit modeling;High-performance embedded systems;Systems and applications;Sensors and systems;Machine learning and AI applications;Communication; Network systems;Power management;Imagers, MEMS, medical, and displays;Radiation front ends (nuclear and space application);Education in circuits, systems, and communications