Showing papers by "Ali A. Minai published in 1998"
TL;DR: An approach for the secure transmission of encrypted messages using chaos and noise is presented and it is shown that a robust and secure system can be obtained.
Abstract: An approach for the secure transmission of encrypted messages using chaos and noise is presented in this paper. The method is based on the synchronization of certain types of chaotic oscillators in response to a common noise input. This allows two distant oscillators to generate identical output which can be used as a key for encryption and decryption of a message signal. The noiselike synchronizing input—which contains no message information—is communicated to identical oscillators in the transmitter and the receiver over a public channel. The encrypted message is also sent over a public channel, while the key is never transmitted at all. The chaotic nature of the oscillators which generate the key and the randomness of the signal driving the process combine to make the recovery of the key by an eavesdropper extremely difficult. We evaluate system performance with respect to security and robustness and show that a robust and secure system can be obtained.
27 citations
04 May 1998
TL;DR: It is argued that the dentate gyrus-hilus system is the locus of context processing, and a simplified neural network model is presented to support the existence of a context-representation system which biases the hippocampal representations.
Abstract: There is now a very extensive body of data on the spatial correlates of neural activity in the hippocampal system of rodents. Place-specific activity is found throughout the system and lesions of various hippocampal regions cause severe deficits on spatial tasks. This has led to the hypothesis that the representation of spatial environments is a primary function of the rodent hippocampers. In this paper, we focus on a set of experimental observations which suggest that spatial representations in the hippocampus proper (CA3/1) are highly context-specific and robust to sensory changes. This suggests the existence of a context-representation system which biases the hippocampal representations. Based on experimental data from the literature, we argue that the dentate gyrus-hilus system is the locus of context processing, and present a simplified neural network model to support this hypothesis.
15 citations
TL;DR: It is shown that there are well-defined domains in which the random input can synchronize even a large population of oscillators within a few hundred steps, suggesting a possible role for chaos in spatially extended physical systems.
Abstract: The research reported in this paper focuses on the response of identical discrete-time neural oscillators to a random telegraph signal input. It is shown that there are well-defined domains in which the random input can synchronize even a large population of oscillators within a few hundred steps. The presence of chaos is shown to be essential for the synchronization, which suggests a possible role for chaos in spatially extended physical systems. The effect of independent noise on the system is also studied.
14 citations
TL;DR: This paper shows that the oscillator responds to the stimulus through a fairly complex set of bifurcations, and shows critical switching between attractors, which can be used to construct very sophisticated dynamic computational elements with well-understood response properties.
Abstract: Based on theoretical issues and neurobiological evidence, considerable interest has recently focused on dynamic computational elements in neural systems. Such elements respond to stimuli by altering their dynamical behavior rather than by changing a scalar output. In particular, neural oscillators capable of chaotic dynamics represent a potentially very rich substrate for complex spatiotemporal information processing. However, the response properties of such systems must be studied in detail before they can be used as computational elements in neural models. In this paper, we focus on the response of a very simple discrete-time neural oscillator model to a fixed input. We show that the oscillator responds to the stimulus through a fairly complex set of bifurcations, and shows critical switching between attractors. This information can be used to construct very sophisticated dynamic computational elements with well-understood response properties. Examples of such elements are presented in the paper. We end with a brief discussion of simple architectures for networks of dynamical elements, and the relevance of our results to neurobiological models.
14 citations
04 May 1998
TL;DR: This paper presents an instance where "noise- like" aperiodic input to a group of chaotic neural oscillators can spontaneously produce a highly organized and potentially useful behavior-synchronization-which is much more difficult to produce with a "signal-like" input.
Abstract: The utility of noise in nonlinear systems is an issue of broad interest, with profound implications about the organization of behavior in complex systems. In this paper, We present an instance where "noise-like" aperiodic input to a group of chaotic neural oscillators can spontaneously produce a highly organized and potentially useful behavior-synchronization-which is much more difficult to produce with a "signal-like" input. In particular, oscillators subject to a fixed signal input can be synchronized quite rapidly by the addition of noise, and, in most cases, increasing noise amplitude enhances the reliability and speed of synchronization.
3 citations