Designing a bidirectional, adaptive neural interface incorporating machine learning capabilities and memristor-enhanced hardware

Shchanikov, S.A.; Zuev, A. D.; Bordanov, Ilya; Danilin, S.N.; Lukoyanov, Vitaly; Королев, Д. С.; Belov, A. I.; Pigareva, Yana; Gladkov, Arseniy; Pimashkin, Alexey; Mikhaylov, A. N.; Kazantsev, Victor B.; Serb, Alexantrou

doi:10.1016/j.chaos.2020.110504

Cited by 57 publications

(25 citation statements)

References 49 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The conclusion hereof is that novel quasi-cognitive mechanisms could be implemented within the decision-making components of an autonomous mobile robot, which can produce special decisions to establish an associative link between the robot and its environment. To implement this process with maximum efficiency, natural cognitive semantics shall be developed, as well as an analog and not algorithmically described method shall be developed for the existence of a decision synthesis mechanism capable of finding its hardware implementation when implementing the considered systems as applied devices based on modern electronic components [9,10].…”

Section: Discussionmentioning

confidence: 99%

Synthesis of special operating decisions as part of adaptive control of a mobile robot

Makarov¹,

Astafiev²

2022

Proceedings of the v International Workshop on Modeling, Information Processing and Computing (MIP: Computing-v 2022)

View full text Add to dashboard Cite

This paper presents theory behind synthesis of special operating decisions in mobile robotics. The authors have developed and implemented an experimental research methodology to substantiate the theoretical and practical significance of the proposed decision structure for incorporation of quasi-cognitive mechanisms in the process of intelligent data processing in such robotics. This paper presents research and testing of a computer model of the abstract decision-making component that analyzes the movement trajectory of a mobile object in the operational space of a mobile robotic system. This approach towards intelligent decisionmaking can be tested for effectiveness by whether it enables the system to detect change in the parameters of the analyzed dynamic object that are important for autonomous analysis of the environment. One finding is that using this novel operating decision structure to improve autonomy contributes to the emergence of a behavior strategy that bypasses the combinatorial methods configured during the development; this improves the system’s adaptability to change in its environment.

show abstract

Section: Discussionmentioning

confidence: 99%

Synthesis of special operating decisions as part of adaptive control of a mobile robot

Makarov¹,

Astafiev²

2022

Proceedings of the v International Workshop on Modeling, Information Processing and Computing (MIP: Computing-v 2022)

View full text Add to dashboard Cite

show abstract

“…As mentioned above, over 50% of the applications of intelligent microfluidics in biotechnology include cell classification, cell screening, cell sorting, the identification of cellular pathology, and the measurement of cellular chemistry [ 3 , 18 , 21 ]. ML can also be used in the analysis, design, and manipulation of continuous or separate fluids in micro-constructs in order to optimize microfluidic platforms [ 14 , 17 , 31 , 32 , 33 ].…”

Section: Systematic Descriptionmentioning

confidence: 99%

Machine Learning-Driven Multiobjective Optimization: An Opportunity of Microfluidic Platforms Applied in Cancer Research

Liu

2022

Cells

View full text Add to dashboard Cite

Cancer metastasis is one of the primary reasons for cancer-related fatalities. Despite the achievements of cancer research with microfluidic platforms, understanding the interplay of multiple factors when it comes to cancer cells is still a great challenge. Crosstalk and causality of different factors in pathogenesis are two important areas in need of further research. With the assistance of machine learning, microfluidic platforms can reach a higher level of detection and classification of cancer metastasis. This article reviews the development history of microfluidics used for cancer research and summarizes how the utilization of machine learning benefits cancer studies, particularly in biomarker detection, wherein causality analysis is useful. To optimize microfluidic platforms, researchers are encouraged to use causality analysis when detecting biomarkers, analyzing tumor microenvironments, choosing materials, and designing structures.

show abstract

“…A single element is responsible for both memorizing and processing information that helps to avoid transferring bottleneck. [ 1 ] Such devices have already been successfully used in nonvolatile memory tasks, [ 2–6 ] as hardware analogs of biological synapses in artificial neural networks, [ 7,8 ] including spiking ones, [ 9–11 ] and biological activity sensors. [ 12 ]…”

Section: Introductionmentioning

confidence: 99%

Pulse Programming of Resistive States of a Benzothieno[3,2‐B][1]‐Benzothiophene‐Based Organic Memristive Device with High Endurance

Прудников

Malakhova

Emelyanov

et al. 2021

Physica Rapid Research Ltrs

View full text Add to dashboard Cite

Organic memristive devices are promising elements to be used in memory tasks, neuromorphic systems, and bioelectronics as hardware analogs of synapses. Among other materials, small molecules are considered in this field as candidates with more adjustable properties and fine chemical structures. Herein, the first organic memristive device based on benzothieno[3,2‐b][1]‐benzothiophene (BTBT) siloxane dimer is reported. The device resistance programming by voltage pulses with various control parameters is demonstrated: amplitude, frequency, and pulse duty cycle. It is proved that the device has at least four different resistive states in each case. In addition, the device shows 2.5 × 104 cycles of sustainable operation in the endurance test with ROFF/RON ratio exceeding 5.

show abstract

Designing a bidirectional, adaptive neural interface incorporating machine learning capabilities and memristor-enhanced hardware

Cited by 57 publications

References 49 publications

Synthesis of special operating decisions as part of adaptive control of a mobile robot

Synthesis of special operating decisions as part of adaptive control of a mobile robot

Machine Learning-Driven Multiobjective Optimization: An Opportunity of Microfluidic Platforms Applied in Cancer Research

Pulse Programming of Resistive States of a Benzothieno[3,2‐B][1]‐Benzothiophene‐Based Organic Memristive Device with High Endurance

Contact Info

Product

Resources

About