Results 151 to 160 of about 40,697 (262)

Model‐Based Time‐Modulated Write Algorithm for 1R Analog Memristive Crossbar Arrays

Advanced Electronic Materials, EarlyView.
A novel model‐based time‐modulated write algorithm efficiently programs analog 1R memristive crossbar arrays by varying pulse duration at a fixed voltage. By leveraging a physics‐based compact model and a dynamic gain mechanism, this approach overcomes device nonlinearities and parasitic effects.
Richard Schroedter, Ahmet Samil Demirkol, Ioannis Messaris, Christian Bruchatz, Eter Mgeladze, Stefan Slesazeck, Thomas Mikolajick, Ronald Tetzlaff   +7 more
wiley   +1 more source

Random Time-Space Coding Metasurfaces for Spatial Control of the Temporal Statistics of Electromagnetic Fields. [PDF]

Adv Sci (Weinh)
Li JC, Bao JH, Liu C, Cui TJ.
europepmc   +1 more source

Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference

Advanced Electronic Materials, EarlyView.
This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho, Dae‐won Kim, Yujin Kim, Jung‐Heum Na, Yuwon Jeong, Dong‐Yeop Lee, Shinhyun Choi   +6 more
wiley   +1 more source

PID Control for Uncertain Systems with Integral Measurements and DoS Attacks Using a Binary Encoding Scheme. [PDF]

Entropy (Basel)
Hou N, Wu Y, Gao H, Hu Z, Bu X.
europepmc   +1 more source

In‐Sensor Computing by Soft Threshold Logic Gates Under Different Humidity Conditions

Advanced Electronic Materials, EarlyView.
Soft nanocomposite materials, based on gold cluster‐assembled thin films implanted in polydimethylsiloxane substrate, can perform reliable processing in ambient environmental conditions. Humidity influences the resistive switching and computational capabilities of the nanocomposites, that can be used as multifunctional material combining sensing ...
Giacomo Nadalini, Paolo Milani, Francesca Borghi   +2 more
wiley   +1 more source

On-Body and Off-Body Communications: A Comparative Study Between Hardware and Simulations. [PDF]

Sensors (Basel)
Oza D, Ramonet AG, Yoshida M, Noguchi T.
europepmc   +1 more source

Efficient In‐Hardware Matrix–Vector Multiplication and Addition Exploiting Bilinearity of Schottky Barrier Transistors Processed on Industrial FDSOI

Advanced Electronic Materials, EarlyView.
ABSTRACT Machine learning and Artificial Intelligence (AI) tasks have stretched traditional hardware to its limits. In‐hardware computation is a novel approach that aims to run complex operations, such as matrix–vector multiplication, directly at the device level for increased efficiency.
Juan P. Martinez, Niladri Bhattacharjee, Yuxuan He, Giulio Galderisi, Brojogopal Sapui, Sara Mannaa, Ian O'Connor, Violetta Sessi, Peter Javorka, Thomas Mikolajick, Jens Trommer   +10 more
wiley   +1 more source

Single-photon advantage in quantum cryptography beyond QKD. [PDF]

Nat Commun
Vajner DA, Kaymazlar K, Drauschke F, Rickert L, von Helversen M, Liu H, Li S, Ni H, Niu Z, Pappa A, Heindel T.   +10 more
europepmc   +1 more source

On the Role of Preprocessing and Memristor Dynamics in Reservoir Computing for Image Classification

Advanced Electronic Materials, EarlyView.
ABSTRACT Reservoir computing (RC) is an emerging recurrent neural network architecture that has attracted growing attention for its low training cost and modest hardware requirements. Memristor‐based circuits are particularly promising for RC, as their intrinsic dynamics can reduce network size and parameter overhead in tasks such as time‐series ...
Rishona Daniels, Duna Wattad, Ronny Ronen, David Saad, Shahar Kvatinsky   +4 more
wiley   +1 more source

Area efficient approximate multiplier based on novel 4:2 compressors and error correction logic. [PDF]

Sci Rep
P KP, V NK.
europepmc   +1 more source