新兴技术
Support vector machines (SVMs) are widely used machine learning models (e.g., in remote sensing), with formulations for both classification and regression tasks. In the last years, with the advent of working quantum annealers, hybrid SVM…
In the classical context, the cooperative game theory concept of the Shapley value has been adapted for post hoc explanations of machine learning models. However, this approach does not easily translate to eXplainable Quantum ML (XQML).…
Biological entities in nature have developed sophisticated communication methods over millennia to facilitate cooperation. Among these entities, plants are some of the most intricate communicators. They interact with each other through…
Photonics is a promising technology to accelerate Deep Neural Networks as it can use optical interconnects to reduce data movement energy and it enables low-energy, high-throughput optical-analog computations. To realize these benefits in a…
Molecular communication (MC) has promising potential and a wide range of applications. However, odor-based communication which is common in nature, has not been sufficiently examined within the context of MC, yet. In this paper, we…
This paper proposes a fast system technology co-optimization (STCO) framework that optimizes power, performance, and area (PPA) for next-generation IC design, addressing the challenges and opportunities presented by novel materials and…
RRAM technology has experienced explosive growth in the last decade, with multiple device structures being developed for a wide range of applications. However, transitioning the technology from the lab into the marketplace requires the…
Although many exciting applications of molecular communication (MC) systems are envisioned to be at microscale, the MC testbeds reported so far are mostly at macroscale. To link the macroworld to the microworld, we propose and demonstrate a…
Active transport such as fluid flow is sought in molecular communication to extend coverage, improve reliability, and mitigate interference. Flow models are often over-simplified, assuming one-dimensional diffusion with constant drift.…
In this paper we propose a novel method of realizing discrete-time (D-T) signal amplification using Nano-Electro-Mechanical (NEMS) devices. The amplifier uses mechanical devices instead of traditional solid-state circuits. The proposed…
1T1R (1-transistor-1-resistor) memory crossbar arrays represent a promising solution for compute-in-memory matrix-vector multiplication accelerators and embedded or storage-class memory. However, the size and scaling of these arrays are…
The integration of LoRaWAN (Long Range Wide Area Network) technology with both active and passive sensors presents a transformative opportunity for the development of smart home systems. This paper explores how active sensors, such as…
There have been a plethora of research on multi-level memory devices, where the resistive random-access memory (RRAM) is a prominent example. Although it is easy to write an RRAM device into multiple (even quasi-continuous) states, it…
Given the growing focus on memristive crossbar-based in-memory computing (IMC) architectures as a potential alternative to current energy-hungry machine learning hardware, the availability of a fast and accurate circuit-level simulation…
The escalating data volume and complexity resulting from the rapid expansion of artificial intelligence (AI), internet of things (IoT) and 5G/6G mobile networks is creating an urgent need for energy-efficient, scalable computing hardware.…
In-memory computing (IMC) architecture emerges as a promising paradigm, improving the energy efficiency of multiply-and-accumulate (MAC) operations within DNNs by integrating the parallel computations within the memory arrays. Various…
This paper designs a molecule harvesting transmitter (TX) model, where the surface of a spherical TX is covered by heterogeneous receptors with different sizes and arbitrary locations. If molecules hit any receptor, they are absorbed by the…
Ising solvers offer a promising physics-based approach to tackle the challenging class of combinatorial optimization problems. However, typical solvers operate in a quadratic energy space, having only pair-wise coupling elements which…
Since performance improvements of computers are stagnating, new technologies and computer paradigms are hot research topics. Memristor-based In-Memory Computing is one of the promising candidates for the post-CMOS era, which comes in many…
Neuro-symbolic artificial intelligence (AI) excels at learning from noisy and generalized patterns, conducting logical inferences, and providing interpretable reasoning. Comprising a 'neuro' component for feature extraction and a 'symbolic'…