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Roman Rybka, Yury Davydov, Danila Vlasov, Alexey Serenko, Alexander Sboev and Vyacheslav Ilyin
Developing a spiking neural network architecture that could prospectively be trained on energy-efficient neuromorphic hardware to solve various data analysis tasks requires satisfying the limitations of prospective analog or digital hardware, i.e., local...
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Ambali Alade Odebowale, Andergachew Mekonnen Berhe, Haroldo T. Hattori and Andrey E. Miroshnichenko
The radiative thermal memristor boasts versatile applications, excelling particularly in contactless thermal sensing, where its unique properties make it ideal for scenarios requiring non-intrusive temperature measurements. Additionally, it holds promise...
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Sergey Shchanikov, Ilya Bordanov, Alexey Kucherik, Evgeny Gryaznov and Alexey Mikhaylov
Arrays of memristive devices coupled with photosensors can be used for capturing and processing visual information, thereby realizing the concept of ?in-sensor computing?. This is a promising concept associated with the development of compact and low-pow...
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Angeliki Bicaku, Maria Sapounaki, Athanasios Kakarountas and Sotiris K. Tasoulis
Throughout the last decades, neuromorphic circuits have incited the interest of scientists, as they are potentially a powerful tool for the treatment of neurological diseases. To this end, it is essential to consider the biological principles of the CNS ...
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Dorian Florescu and Daniel Coca
Digital filtering is a fundamental technique in digital signal processing, which operates on a digital sequence without any information on how the sequence was generated. This paper proposes a methodology for designing the equivalent of digital filtering...
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Ali Siddique, Jingqi Sun, Kung Jui Hou, Mang I. Vai, Sio Hang Pun and Muhammad Azhar Iqbal
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Arash Khajooei Nejad, Mohammad (Behdad) Jamshidi and Shahriar B. Shokouhi
This paper introduces Tensor-Organized Memory (TOM), a novel neuromorphic architecture inspired by the human brain?s structural and functional principles. Utilizing spike-timing-dependent plasticity (STDP) and Hebbian rules, TOM exhibits cognitive behavi...
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Arash Khajooei, Mohammad (Behdad) Jamshidi and Shahriar B. Shokouhi
Although the Metaverse is becoming a popular technology in many aspects of our lives, there are some drawbacks to its implementation on clouds, including long latency, security concerns, and centralized infrastructures. Therefore, designing scalable Meta...
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John S. Venker, Luke Vincent and Jeff Dix
A Spiking Neural Network (SNN) is realized within a 65 nm CMOS process to demonstrate the feasibility of its constituent cells. Analog hardware neural networks have shown improved energy efficiency in edge computing for real-time-inference applications, ...
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Wallace Moreira Bessa and Gabriel da Silva Lima
Memristive neuromorphic systems represent one of the most promising technologies to overcome the current challenges faced by conventional computer systems. They have recently been proposed for a wide variety of applications, such as nonvolatile computer ...
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