Symmetry in Chaotic Systems and Circuits

Symmetry can play an important role in the field of nonlinear systems and especially in the design of nonlinear circuits that produce chaos. Therefore, this Special Issue, titled “Symmetry in Chaotic Systems and Circuits”, presents the latest scientific advances in nonlinear chaotic systems and circuits that introduce various kinds of symmetries. Applications of chaotic systems and circuits with symmetries, or with a deliberate lack of symmetry, are also presented in this Special Issue. The volume contains 14 published papers from authors around the world. This reflects the high impact of this Special Issue

A Survey on Reservoir Computing and its Interdisciplinary Applications Beyond Traditional Machine Learning

Reservoir computing (RC), first applied to temporal signal processing, is a recurrent neural network in which neurons are randomly connected. Once initialized, the connection strengths remain unchanged. Such a simple structure turns RC into a non-linear dynamical system that maps low-dimensional inputs into a high-dimensional space. The model's rich dynamics, linear separability, and memory capacity then enable a simple linear readout to generate adequate responses for various applications. RC spans areas far beyond machine learning, since it has been shown that the complex dynamics can be realized in various physical hardware implementations and biological devices. This yields greater flexibility and shorter computation time. Moreover, the neuronal responses triggered by the model's dynamics shed light on understanding brain mechanisms that also exploit similar dynamical processes. While the literature on RC is vast and fragmented, here we conduct a unified review of RC's recent developments from machine learning to physics, biology, and neuroscience. We first review the early RC models, and then survey the state-of-the-art models and their applications. We further introduce studies on modeling the brain's mechanisms by RC. Finally, we offer new perspectives on RC development, including reservoir design, coding frameworks unification, physical RC implementations, and interaction between RC, cognitive neuroscience and evolution.Comment: 51 pages, 19 figures, IEEE Acces

Low Power IoT based Automated Manhole Cover Monitoring System as a Smart City application

With the increased population in the big cities, Internet of Things (IoT) devices to be used as automated monitoring systems are required in many of the Smart city’s applications. Monitoring road infrastructure such as a manhole cover (MC) is one of these applications. Automating monitoring manhole cover structure has become more demanding, especially when the number of MC failure increases rapidly: it affects the safety, security and the economy of the society. Only 30% of the current MC monitoring systems are automated with short lifetime in comparison to the lifetime of the MC, without monitoring all the MC issues and without discussing the challenges of the design from IoT device design point of view. Extending the lifetime of a fully automated IoT-based MC monitoring system from circuit design point of view was studied and addressed in this research. The main circuit that consumes more power in the IoT-based MC monitoring system is the analogue to digital converter (ADC) found at the data acquisition module (DAQ). In several applications, the compressive sensing (CS) technique proved its capability to reduce the power consumption for ADC. In this research, CS has been investigated and studied deeply to reach the aim of the research. CS based ADC is named analogue to information converter (AIC). Because the heart of the AIC is the pseudorandom number generator (PRNG), several researchers have used it as a key to secure the data, which makes AIC more suitable for IoT device design. Most of these PRNG designs for AIC are hardware implemented in the digital circuit design. The presence of digital PRNG at the AIC analogue front end requires: a) isolating digital and analogue parts, and b) using two different power supplies and grounds for analogue and digital parts. On the other hand, analogue circuit design becomes more demanding for the sake of the power consumption, especially after merging the analogue circuit design with other fields such as neural networks and neuroscience. This has motivated the researcher to propose two low-power analogue chaotic oscillators to replace digital PRNG using opamp Schmitt Trigger. The proposed systems are based on a coupling oscillator concept. The design of the proposed systems is based on: First, two new modifications for the well-known astable multivibrator using opamp Schmitt trigger. Second, the waveshaping design technique is presented to design analogue chaotic oscillators instead of starting with complex differential equations as it is the case for most of the chaotic oscillator designs. This technique helps to find easy steps and understanding of building analogue chaotic oscillators for electronic circuit designers. The proposed systems used off the shelf components as a proof of concept. The proposed systems were validated based on: a) the range of the temperature found beneath a manhole cover, and b) the signal reconstruction under the presence and the absence of noise. The results show decent performance of the proposed system from the power consumption point of view, as it can exceed the lifetime of similar two opamps based Jerk chaotic oscillators by almost one year for long lifetime applications such as monitoring MC using Li-Ion battery. Furthermore, in comparison to PRNG output sequence generated by a software algorithm used in AIC framework in the presence of the noise, the first proposed system output sequence improved the signal reconstruction by 6.94%, while the second system improved the signal reconstruction by 17.83

東北大学電気通信研究所研究活動報告 第29号(2022年度)

紀要類（bulletin）departmental bulletin pape

Proceedings of the 7th Sound and Music Computing Conference

Proceedings of the SMC2010 - 7th Sound and Music Computing Conference, July 21st - July 24th 2010