197 research outputs found

    Neuro-memristive Circuits for Edge Computing: A review

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    The volume, veracity, variability, and velocity of data produced from the ever-increasing network of sensors connected to Internet pose challenges for power management, scalability, and sustainability of cloud computing infrastructure. Increasing the data processing capability of edge computing devices at lower power requirements can reduce several overheads for cloud computing solutions. This paper provides the review of neuromorphic CMOS-memristive architectures that can be integrated into edge computing devices. We discuss why the neuromorphic architectures are useful for edge devices and show the advantages, drawbacks and open problems in the field of neuro-memristive circuits for edge computing

    Memristor-based Random Access Memory: The delayed switching effect could revolutionize memory design

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    Memristor’s on/off resistance can naturally store binary bits for non-volatile memories. In this work, we found that memristor’s another peculiar feature that the switching takes place with a time delay (we name it “the delayed switching”) can be used to selectively address any desired memory cell in a crossbar array. The analysis shows this is a must-be in a memristor with a piecewise-linear ?-q curve. A “circuit model”-based experiment has verified the delayed switching feature. It is demonstrated that memristors can be packed at least twice as densely as semiconductors, achieving a significant breakthrough in storage density

    A Circuit-Based Neural Network with Hybrid Learning of Backpropagation and Random Weight Change Algorithms.

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    A hybrid learning method of a software-based backpropagation learning and a hardware-based RWC learning is proposed for the development of circuit-based neural networks. The backpropagation is known as one of the most efficient learning algorithms. A weak point is that its hardware implementation is extremely difficult. The RWC algorithm, which is very easy to implement with respect to its hardware circuits, takes too many iterations for learning. The proposed learning algorithm is a hybrid one of these two. The main learning is performed with a software version of the BP algorithm, firstly, and then, learned weights are transplanted on a hardware version of a neural circuit. At the time of the weight transplantation, a significant amount of output error would occur due to the characteristic difference between the software and the hardware. In the proposed method, such error is reduced via a complementary learning of the RWC algorithm, which is implemented in a simple hardware. The usefulness of the proposed hybrid learning system is verified via simulations upon several classical learning problems

    Canards from Chua's circuit

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    The aim of this work is to extend Beno\^it's theorem for the generic existence of "canards" solutions in singularly perturbed dynamical systems of dimension three with one fast variable to those of dimension four. Then, it is established that this result can be found according to the Flow Curvature Method. Applications to Chua's cubic model of dimension three and four enable to state the existence of "canards" solutions in such systems.Comment: arXiv admin note: text overlap with arXiv:1408.489

    Chaos in a Switched-Capacitor Circuit

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    We report chaotic phenomena observed from a simple nonlinear switched-capacitor circuit. The experimentally measured bifurcation tree diagram reveals a period-doubling route to chaos. This circuit is described by a first-order discrete equation which can be transformed into the logistic map whose chaotic dynamics is well known.National Science Foundation ECS-8542885Comisión Interministerial de Ciencia y Tecnología 0245/81Office of Naval Research under Contract NOOO14-76-C-057

    Global homeomorphism of vector-valued functions

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    The role of synchronization in digital communications using chaos - Part II: Chaotic modulation and chaotic synchronization.

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    For pt. I see ibid., vol. 44, p. 927-36 (1997). In a digital communications system, data are transmitted from one location to another by mapping bit sequences to symbols, and symbols to sample functions of analog waveforms. The analog waveform passes through a bandlimited (possibly time-varying) analog channel, where the signal is distorted and noise is added. In a conventional system the analog sample functions sent through the channel are weighted sums of one or more sinusoids; in a chaotic communications system the sample functions are segments of chaotic waveforms. At the receiver, the symbol may be recovered by means of coherent detection, where all possible sample functions are known, or by noncoherent detection, where one or more characteristics of the sample functions are estimated. In a coherent receiver, synchronization is the most commonly used technique for recovering the sample functions from the received waveform. These sample functions are then used as reference signals for a correlator. Synchronization-based coherent receivers have advantages over noncoherent receivers in terms of noise performance, bandwidth efficiency (in narrow-band systems) and/or data rate (in chaotic systems). These advantages are lost if synchronization cannot be maintained, for example, under poor propagation conditions. In these circumstances, communication without synchronization may be preferable. The theory of conventional telecommunications is extended to chaotic communications, chaotic modulation techniques and receiver configurations are surveyed, and chaotic synchronization schemes are describe

    The role of synchronization in digital communications using chaos - part I: fundamentals of digital communications.

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    In a digital communications system, data is transmitted from one location to another by mapping bit sequences to symbols, and symbols to sample functions of analog waveforms. The analog waveform passes through a bandlimited (possibly time-varying) analog channel, where the signal is distorted and noise is added. In a conventional system the analog sample functions sent through the channel are weighted sums of one or more sinusoids; in a chaotic communications system, the sample functions are segments of chaotic waveforms. At the receiver, the symbol may be recovered by means of coherent detection, where all possible sample functions are known, or by noncoherent detection, where one or more characteristics of the sample functions are estimated. In a coherent receiver, synchronization is the most commonly used technique for recovering the sample functions from the received waveform. These sample functions are then used as reference signals for a correlator. Synchronization-based receivers have advantages over noncoherent ones in terms of noise performance and bandwidth efficiency. These advantages are lost if synchronization cannot be maintained, for example, under poor propagation conditions. In these circumstances, communication without synchronization may be preferable. The main aim of this paper is to provide a unified approach for the analysis and comparison of conventional and chaotic communications systems. In Part I, the operation of sinusoidal communications techniques is surveyed in order to clarify the role of synchronization and to classify possible demodulation methods for chaotic communication
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