Alon Ascoli - Academia.edu (original) (raw)

Papers by Alon Ascoli

2015 IEEE 15th International Conference on Nanotechnology (IEEE-NANO), 2015

The nanoscale memristor is a serious candidate to become the core element of novel ultra-high den... more The nanoscale memristor is a serious candidate to become the core element of novel ultra-high density low-power non-volatile memories and innovative pattern recognition systems based upon oscillatory associative and dynamic memories. Furthermore, this peculiar device also has the potential to capture the behavior of a biological synapse more efficiently and accurately than any conventional electronic emulator since it exhibits the unique capability of performing computation and storing data at the same physical location and at same time. In addition, it has a flux-controlled conductance which is analogous to the ionic flow-controlled synaptic weight. This chapter gives some insight into the mechanisms underlying the emergence of synchronization between two oscillatory cells coupled through an ideal memristor. The investigations show that in some cases the nonlinear dynamics of the memristor play a key role in the development of synchronous oscillations in the two oscillators. This work sheds light on some aspects of the nonlinear behavior of the still largely unexplored memristor, which is doomed to make an impact in integrated circuit design in the years to come.

2012 13th International Workshop on Cellular Nanoscale Networks and Their Applications, Aug 1, 2012

ABSTRACT

IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 2015

2015 International Joint Conference on Neural Networks (IJCNN), 2015

2015 European Conference on Circuit Theory and Design (ECCTD), 2015

Floating-capacitor implementations of differential-output log-domain circuits exhibit externally ... more Floating-capacitor implementations of differential-output log-domain circuits exhibit externally nonlinear behavior. However, the cause of these dynamics may differ from case to case. In a floating-capacitor class AB log-domain parallel resonator it was the finite forward-current gain of a pair of cross-coupled transistors that played a crucial role in the emergence of the nonlinearities. On the other hand, it was recently proved that in floating-capacitor log-domain LC-ladders the BJT parasitic capacitances considerably affect the dynamics and must be taken into account for modeling purposes, no matter how small they are with respect to the floating capacitors. This work proves that, as was the case for the parallel resonator, the base currents of a number of transistors are responsible for the nonlinear dynamics of a class AB log-domain exponential state-space filter. This is achieved by presenting and validating the simplest mathematical model able to capture the nonlinear behavi...

International Journal of Circuit Theory and Applications

Log-domain filters are an intriguing form of externally linear, internally nonlinear current-mode... more Log-domain filters are an intriguing form of externally linear, internally nonlinear current-mode circuits, in which a compression stage is first used to convert the input currents to the logarithmic domain, then analogue processing is carried out on the resulting voltages, and finally input–output linearity is restored by mapping the output voltages to current form through an expansion stage. The compressing and expanding operations confer on log-domain filters a number of desirable features, but they may be responsible for the loss of external linearity. In this paper, sufficient conditions for the external linearity of log-domain LC-ladders are established, and the local nature of this external linearity is highlighted. Certain log-domain LC-ladders employing floating capacitors may exhibit externally nonlinear behaviour even for zero input and very small initial conditions. We show how transistor parasitic capacitances are central to the emergence of this behaviour, and must be ...

Journal of the Franklin Institute, 2015

ABSTRACT

2015 IEEE International Symposium on Circuits and Systems (ISCAS), 2015

International Journal of Circuit Theory and Applications, 2015

International Journal of Circuit Theory and Applications, 2015

IEEE Transactions on Circuits and Systems I: Regular Papers, 2015

ABSTRACT This work elucidates some aspects of the nonlinear dynamics of a thermally-activated loc... more ABSTRACT This work elucidates some aspects of the nonlinear dynamics of a thermally-activated locally-active memristor based on a micro-structure consisting of a bi-layer of rmNb2rmO5{rm Nb}_{2}{rm O}_{5}rmNb2rmO5 and rmNb2rmOx{rm Nb}_{2}{rm O}_{x}rmNb2rmOx materials. Through application of techniques from the theory of nonlinear dynamics to an accurate and simple mathematical model for the device, we gained a deep insight into the mechanisms at the origin of the emergence of local activity in the memristor. This theoretical study sets a general constraint on the biasing arrangement for the stabilization of the negative differential resistance effect in locally active memristors and provides a theoretical justification for an unexplained phenomenon observed at HP labs. As proof-of-principle, the constraint was used to enable a memristor to induce sustained oscillations in a one port cell. The capability of the oscillatory cell to amplify infinitesimal fluctuations of energy was theoretically and experimentally proved.

2013 European Conference on Circuit Theory and Design (ECCTD), 2013

ABSTRACT

2011 20th European Conference on Circuit Theory and Design (ECCTD), 2011

Networks made up of bio-inspired neuron oscilla- tory circuits with nanoscale memristors may achi... more Networks made up of bio-inspired neuron oscilla- tory circuits with nanoscale memristors may achieve the large connectivity and highly parallel processing power of biological systems. Memristor also has potential to reproduce the behavior of a biological synapse. As in a living creature the weight of a synapse is adapted by ionic flow through it, so the conductance of a memristor

2013 IEEE International Symposium on Circuits and Systems (ISCAS2013), 2013

ABSTRACT Biological neural systems use self- reconfigurable and self-learning primitive elements ... more ABSTRACT Biological neural systems use self- reconfigurable and self-learning primitive elements (synapses) to extract relevant information from complex and noisy environments, to detect specific spatio-temporal patterns in the data of interest and to compute and simultaneously store some significant features. All these desirable attributes may be realized by using two-terminal elements, memristors (memory resistors), which most closely resemble biological synapses. This article is organized according to the rule of the ISCAS2013 special session having the same title. We present a short summary of the state-of-the-art of memristor theory and Hodgkin-Huxley neural model. In addition, we briefly introduce a comprehensive nonlinear circuit-theoretic foundation for a novel circuit implementation of the Hodgkin-Huxley neural model with memristors.

The nanoscale memristor is a serious candidate to become the core element of novel ultra-high den... more The nanoscale memristor is a serious candidate to become the core element of novel ultra-high density low-power non-volatile memories and innovative pattern recognition systems based upon oscillatory associative and dynamic memories. Furthermore, this peculiar device also has the potential to capture the behavior of a biological synapse more efficiently and accurately than any conventional electronic emulator since it exhibits the unique capability of performing computation and storing data at the same physical location and at same time. In addition, it has a flux-controlled conductance which is analogous to the ionic flow-controlled synaptic weight. This chapter gives some insight into the mechanisms underlying the emergence of synchronization between two oscillatory cells coupled through an ideal memristor. The investigations show that in some cases the nonlinear dynamics of the memristor play a key role in the development of synchronous oscillations in the two oscillators. This work sheds light on some aspects of the nonlinear behavior of the still largely unexplored memristor, which is doomed to make an impact in integrated circuit design in the years to come.

2012 IEEE/IFIP 20th International Conference on VLSI and System-on-Chip (VLSI-SoC), 2012

ABSTRACT

2015 IEEE 15th International Conference on Nanotechnology (IEEE-NANO), 2015

The nanoscale memristor is a serious candidate to become the core element of novel ultra-high den... more The nanoscale memristor is a serious candidate to become the core element of novel ultra-high density low-power non-volatile memories and innovative pattern recognition systems based upon oscillatory associative and dynamic memories. Furthermore, this peculiar device also has the potential to capture the behavior of a biological synapse more efficiently and accurately than any conventional electronic emulator since it exhibits the unique capability of performing computation and storing data at the same physical location and at same time. In addition, it has a flux-controlled conductance which is analogous to the ionic flow-controlled synaptic weight. This chapter gives some insight into the mechanisms underlying the emergence of synchronization between two oscillatory cells coupled through an ideal memristor. The investigations show that in some cases the nonlinear dynamics of the memristor play a key role in the development of synchronous oscillations in the two oscillators. This work sheds light on some aspects of the nonlinear behavior of the still largely unexplored memristor, which is doomed to make an impact in integrated circuit design in the years to come.

2012 13th International Workshop on Cellular Nanoscale Networks and Their Applications, Aug 1, 2012

ABSTRACT

IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 2015

2015 International Joint Conference on Neural Networks (IJCNN), 2015

2015 European Conference on Circuit Theory and Design (ECCTD), 2015

Floating-capacitor implementations of differential-output log-domain circuits exhibit externally ... more Floating-capacitor implementations of differential-output log-domain circuits exhibit externally nonlinear behavior. However, the cause of these dynamics may differ from case to case. In a floating-capacitor class AB log-domain parallel resonator it was the finite forward-current gain of a pair of cross-coupled transistors that played a crucial role in the emergence of the nonlinearities. On the other hand, it was recently proved that in floating-capacitor log-domain LC-ladders the BJT parasitic capacitances considerably affect the dynamics and must be taken into account for modeling purposes, no matter how small they are with respect to the floating capacitors. This work proves that, as was the case for the parallel resonator, the base currents of a number of transistors are responsible for the nonlinear dynamics of a class AB log-domain exponential state-space filter. This is achieved by presenting and validating the simplest mathematical model able to capture the nonlinear behavi...

International Journal of Circuit Theory and Applications

Log-domain filters are an intriguing form of externally linear, internally nonlinear current-mode... more Log-domain filters are an intriguing form of externally linear, internally nonlinear current-mode circuits, in which a compression stage is first used to convert the input currents to the logarithmic domain, then analogue processing is carried out on the resulting voltages, and finally input–output linearity is restored by mapping the output voltages to current form through an expansion stage. The compressing and expanding operations confer on log-domain filters a number of desirable features, but they may be responsible for the loss of external linearity. In this paper, sufficient conditions for the external linearity of log-domain LC-ladders are established, and the local nature of this external linearity is highlighted. Certain log-domain LC-ladders employing floating capacitors may exhibit externally nonlinear behaviour even for zero input and very small initial conditions. We show how transistor parasitic capacitances are central to the emergence of this behaviour, and must be ...

Journal of the Franklin Institute, 2015

ABSTRACT

2015 IEEE International Symposium on Circuits and Systems (ISCAS), 2015

International Journal of Circuit Theory and Applications, 2015

International Journal of Circuit Theory and Applications, 2015

IEEE Transactions on Circuits and Systems I: Regular Papers, 2015

ABSTRACT This work elucidates some aspects of the nonlinear dynamics of a thermally-activated loc... more ABSTRACT This work elucidates some aspects of the nonlinear dynamics of a thermally-activated locally-active memristor based on a micro-structure consisting of a bi-layer of rmNb2rmO5{rm Nb}_{2}{rm O}_{5}rmNb2rmO5 and rmNb2rmOx{rm Nb}_{2}{rm O}_{x}rmNb2rmOx materials. Through application of techniques from the theory of nonlinear dynamics to an accurate and simple mathematical model for the device, we gained a deep insight into the mechanisms at the origin of the emergence of local activity in the memristor. This theoretical study sets a general constraint on the biasing arrangement for the stabilization of the negative differential resistance effect in locally active memristors and provides a theoretical justification for an unexplained phenomenon observed at HP labs. As proof-of-principle, the constraint was used to enable a memristor to induce sustained oscillations in a one port cell. The capability of the oscillatory cell to amplify infinitesimal fluctuations of energy was theoretically and experimentally proved.

2013 European Conference on Circuit Theory and Design (ECCTD), 2013

ABSTRACT

2011 20th European Conference on Circuit Theory and Design (ECCTD), 2011

Networks made up of bio-inspired neuron oscilla- tory circuits with nanoscale memristors may achi... more Networks made up of bio-inspired neuron oscilla- tory circuits with nanoscale memristors may achieve the large connectivity and highly parallel processing power of biological systems. Memristor also has potential to reproduce the behavior of a biological synapse. As in a living creature the weight of a synapse is adapted by ionic flow through it, so the conductance of a memristor

2013 IEEE International Symposium on Circuits and Systems (ISCAS2013), 2013

ABSTRACT Biological neural systems use self- reconfigurable and self-learning primitive elements ... more ABSTRACT Biological neural systems use self- reconfigurable and self-learning primitive elements (synapses) to extract relevant information from complex and noisy environments, to detect specific spatio-temporal patterns in the data of interest and to compute and simultaneously store some significant features. All these desirable attributes may be realized by using two-terminal elements, memristors (memory resistors), which most closely resemble biological synapses. This article is organized according to the rule of the ISCAS2013 special session having the same title. We present a short summary of the state-of-the-art of memristor theory and Hodgkin-Huxley neural model. In addition, we briefly introduce a comprehensive nonlinear circuit-theoretic foundation for a novel circuit implementation of the Hodgkin-Huxley neural model with memristors.

The nanoscale memristor is a serious candidate to become the core element of novel ultra-high den... more The nanoscale memristor is a serious candidate to become the core element of novel ultra-high density low-power non-volatile memories and innovative pattern recognition systems based upon oscillatory associative and dynamic memories. Furthermore, this peculiar device also has the potential to capture the behavior of a biological synapse more efficiently and accurately than any conventional electronic emulator since it exhibits the unique capability of performing computation and storing data at the same physical location and at same time. In addition, it has a flux-controlled conductance which is analogous to the ionic flow-controlled synaptic weight. This chapter gives some insight into the mechanisms underlying the emergence of synchronization between two oscillatory cells coupled through an ideal memristor. The investigations show that in some cases the nonlinear dynamics of the memristor play a key role in the development of synchronous oscillations in the two oscillators. This work sheds light on some aspects of the nonlinear behavior of the still largely unexplored memristor, which is doomed to make an impact in integrated circuit design in the years to come.

2012 IEEE/IFIP 20th International Conference on VLSI and System-on-Chip (VLSI-SoC), 2012

ABSTRACT