Design of Artificial Neurons of Memristive Neuromorphic Networks Based on Biological Neural Dynamics and Structures

© 2024, IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. This is the accepted manuscript version of a conference paper which has been published in final form at https://doi.org/10.1109/TCSI.2023.3332496Memristive neuromorphic networks have great potentialand advantage in both technology and computationalprotocols for artificial intelligence. Efficient hardware design ofbiological neuron models forms the core of research problems inneuromorphic networks. However, most of the existing researchhas been based on logic or integrated circuit principles, limitedto replicating simple integrate-and-fire behaviors, while morecomplex firing characteristics have relied on the inherent propertiesof the devices themselves, without support from biologicalprinciples. This paper proposes a memristor-based neuron circuitsystem (MNCS) according to the microdynamics of neuronsand complex neural cell structures. It leverages the nonlinearityand non-volatile characteristics of memristors to simulate thebiological functions of various ion channels. It is designed basedon the Hodgkin-Huxley (HH) model circuit, and the parametersare adjusted according to each neuronal firing mechanism. BothPSpice simulations and practical experiments have demonstratedthat MNCS can replicate 24 types of repeating biological neuronalbehaviors. Furthermore, the results from the Joint Inter-spikeInterval(JISI) experiment indicate that as the background noiseincreases, MNCS exhibits pulse emission characteristics similarto those of biological neurons.Peer reviewe

Low Voltage Current Mode Switched-Current-Mirror Mixer

A new CMOS active mixer topology can operate at 1 V supply voltage by use of SCM (switched currentmirror). Such current-mode mixer requires less voltage headroom with good linearization. Mixing is achieved with four improved current mirrors, which are alternatively activated. For ideal switching, the operation is equivalent to a conventional active mixer. This paper analyzes the performance of the SCM mixer, in comparison with the conventional mixer, demonstrating competitive performance at a lower supply voltage. Moreover, the new mixer’s die, without any passive components, is very small, and the conversion gain is easy to adjust. An experimental prototype was designed and simulated in standard chartered 0.18μm RF CMOS Process with Spectre in Cadence Design Systems. Experimental results show satisfactory mixer performance at 2.4 GHz

A family of memristive multibutterfly chaotic systems with multidirectional initial-based offset boosting

© 2023 Elsevier Ltd. All rights reserved. This is the accepted manuscript version of an article which has been published in final form at https://doi.org/10.1016/j.chaos.2023.113518Memristors are commonly used to construct memristive chaotic systems with complex dynamics because of their strong nonlinearity and unique memory effects. In this paper, a simplified multi-piecewise memristor is applied for designing a family of memristive multibutterfly chaotic systems (MMBCSs). By coupling different numbers of the simplified multi-piecewise memristors into a modified Sprott C system, three MMBCSs are constructed. Theoretical analysis and numerical simulations show that the three MMBCSs can not only generate connected 1D(direction)-, 2D(plane)-, and 3D(space)-multibutterfly chaotic attractors (MBCAs), respectively, but also can respectively produce unconnected 1D-, 2D-, and 3D-MBCAs. Also, the number and position of butterfly attractors can be easily controlled by switching the memristor’s integer parameters and initial states, respectively. More importantly, the constructed three MMBCSs exhibit different initial-based offset boosting including 1D-, 2D-, and 3D-boosting behaviors, respectively. Especially, the 3D-initial-offset behavior is found in chaotic systems at the first time. Furthermore, we further implement the physical circuit of the three MMBCSs, and various typical dynamical behaviors are demonstrated by hardware experiments and Multisim simulations. Finally, a medical image encryption solution for online medical treatment is designed based on the proposed MMBCSs.Peer reviewe

Chaos-Based Engineering Applications with a 6D Memristive Multistable Hyperchaotic System and a 2D SF-SIMM Hyperchaotic Map

In recent years, the research of chaos theory has developed from simple cognition and analysis to practical engineering application. In particular, hyperchaotic systems with more complex and changeable chaotic characteristics are more sensitive and unpredictable, so they are widely used in more fields. In this paper, two important engineering applications based on hyperchaos pseudorandom number generator (PRNG) and image encryption are studied. Firstly, the coupling 6D memristive hyperchaotic system and a 2D SF-SIMM discrete hyperchaotic mapping are used as the double entropy source structure. The double entropy source structure can realize a new PRNG that meets the security requirements, which can pass the NIST statistical test when the XOR postprocessing method is used. Secondly, based on the double entropy source structure, a new image encryption algorithm is proposed. The algorithm uses the diffusion-scrambling-diffusion encryption scheme to realize the conversion from the original plaintext image to the ciphertext image. Finally, we analyze the security of the proposed PRNG and image encryption mechanism, respectively. The results show that the proposed PRNG has good statistical output characteristics and the proposed image encryption scheme has high security, so they can be effectively applied in the field of information security and encryption system

Dynamic Analysis and Audio Encryption Application in IoT of a Multi-Scroll Fractional-Order Memristive Hopfield Neural Network

Fractional-order chaotic systems are widely used in the field of encryption because of its initial value sensitivity and historical memory. In this paper, the fractional-order definition of Caputo is introduced based on a nonideal flux-controlled memristive Hopfield neural network model, when changing the parameters of the fractional-order memristive Hopfield neural network (FMHNN) can generate a different amount of multi-scroll attractors. Some dynamical behaviors are investigated by numerical simulation, especially analyzed coexistence and bifurcation under different orders and different coupling strengths. The results show that the chaotic system of FMHNN has abundant dynamic behaviors. In addition, a chaotic audio encryption scheme under a Message Queueing Telemetry Transport (MQTT) protocol is proposed and implemented by Raspberry Pi; the audio encryption system based on FMHNN has a broad future in intelligent home and other IoT applications

Anti-Obesity and Gut Microbiota Regulation Effects of Phospholipids from the Eggs of Crab, Portunus Trituberculatus, in High Fat Diet-Fed Mice

There are resourceful phospholipids in the eggs of the crab, Portunus trituberculatus (Pt-PL). However, their components and bioactivities regarding obesity were unclear. Here, we investigated the composition of Pt-PL and their fatty acids. Moreover, its effects on obesity and gut microbiota were also evaluated in high fat diet (HFD)-fed mice. The results showed that Pt-PL contained 12 kinds of phospholipids, mainly including phosphatidylcholine (PC, 32.28%), phosphatidylserine (PS, 26.51%), phosphatidic acid (PA, 19.61%), phosphatidylethanolamine (PE, 8.81%), and phosphatidylinositol (PI, 7.96%). Polyunsaturated fatty acids (PUFAs) predominated in the fatty acids components of Pt-PL, especially eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA). Animal experiments demonstrated that Pt-PL significantly alleviated body weight gain, adipose gain, hepatic gain, fasting blood glucose, serum insulin, lipid levels in serum and the liver, and systematic inflammation in HFD-fed mice. Furthermore, Pt-PL regulated gut microbiota, especially in a dramatic reduction in the ratio of Firmicutes to Bacteroidetes at phylum level, as well as significant amelioration in their subordinate categories. Pt-PL reduced fecal lipopolysaccharide and total bile acids, and elevated fecal short chain fatty acid (SCFA) concentrations, particularly acetate and butyrate. These findings suggest that Pt-PL possesses anti-obesity effects and can alter gut microbiota owing to the abundance of PUFAs. Therefore, Pt-PL may be developed as an effective food supplement for anti-obesity and regulation of human gut health

Dynamic Analysis and Audio Encryption Application in IoT of a Multi-Scroll Fractional-Order Memristive Hopfield Neural Network

Fractional-order chaotic systems are widely used in the field of encryption because of its initial value sensitivity and historical memory. In this paper, the fractional-order definition of Caputo is introduced based on a nonideal flux-controlled memristive Hopfield neural network model, when changing the parameters of the fractional-order memristive Hopfield neural network (FMHNN) can generate a different amount of multi-scroll attractors. Some dynamical behaviors are investigated by numerical simulation, especially analyzed coexistence and bifurcation under different orders and different coupling strengths. The results show that the chaotic system of FMHNN has abundant dynamic behaviors. In addition, a chaotic audio encryption scheme under a Message Queueing Telemetry Transport (MQTT) protocol is proposed and implemented by Raspberry Pi; the audio encryption system based on FMHNN has a broad future in intelligent home and other IoT applications

Low Molecular Weight, 4-O-Sulfation, and Sulfation at Meta-Fucose Positively Promote the Activities of Sea Cucumber Fucoidans on Improving Insulin Resistance in HFD-Fed Mice

Fucoidans from sea cucumber (SC-FUC) have been proven to alleviate insulin resistance in several species. However, there are few studies that clarify the relationship between their structure and bioactivity. The present study evaluated the influence of molecular weight (Mw), sulfation concentrations (Cs), and sulfation position on improving insulin resistance using SC-FUC. Results showed that fucoidans with lower Mw exerted stronger effects. Having a similar Mw, Acaudina molpadioides fucoidans (Am-FUC) with lower Cs and Holothuria tubulosa fucoidans with higher Cs showed similar activities. However, Isostichopus badionotus fucoidans (higher Cs) activity was superior to that of low-Mw Thelenota ananas fucoidans (Ta-LFUC, lower Cs). Eliminating the effects of Mw and Cs, the bioactivity of Am-FUC with sulfation at meta-fucose exceeded that of Ta-FUC with sulfation at ortho-position. Moreover, the effects of Pearsonothuria graeffei fucoidans with 4-O-sulfation were superior to those of Am-LFUC with 2-O-sulfation. These data indicate that low Mw, 4-O-sulfation, and sulfation at meta-fucose contributed considerably to insulin resistance alleviation by SC-FUC, which could accelerate the development of SC-FUC as a potential food supplement to alleviate insulin resistance