A Low Power Current-Mode Binary-Tree WTA / LTA Circuit for Kohonen Neural Networks

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Ultralow-power sensing with inference functionality embedded in sensor nodes is essential for enabling the emerging pervasive intelligence. For acoustic inference sensing, the feature extraction can take advantage of power-efficient analog circuits. Howeve ...

DC-DC converters based on Application Specific Integrated Circuits (ASICs) have been developed in this doctoral work for the High-Luminosity Large Hadron Collider (HL-LHC) experiments at CERN. They step down the voltage from a 2.5 V line and supply a load ...

Wireless implantable neural recording chips enable multichannel data acquisition with high spatiotemporal resolution in situ. Recently, the use of machine learning approaches on neural data for diagnosis and prosthesis control have renewed the interest in ...

On-chip signal processing at microwave frequencies is key for modern mobile communication. When one aims at small footprints, low power consumption, reprogrammable filters, and delay lines, magnons in low-damping ferrimagnets offer great promise. Ferromagn ...

Modern mesh generation addresses the development of robust algorithms that construct a discrete representation of the geometry into polytopal elements conforming to divergent properties: (i) fidelity to complex geometrical features, (ii) support for high s ...

Harnessing quantum randomness for the generation of random numbers is an important concept crucial for information security and many other computer-related applications. Quantum random number generators (QRNGs) are evolving from bulky, slow, and expensive ...

This paper presents the design of an application-specific integrated circuit (ASIC) with all the necessary electronic blocks to read out and control Conjugate Surfaces Flexure Hinge (CSFH) microgrippers. The ASIC was fabricated using a high-voltage 0.35 mu ...

Total ionizing radiation compromises electrical characteristics of microelectronic devices and even causes functional failures of integrated circuits. It has been identified as a potential threat to electronic components, especially those in high-energy ph ...

We propose an online algorithm for sequential learning in the contextual multiarmed bandit setting. Our approach is to partition the context space and, then, optimally combine all of the possible mappings between the partition regions and the set of bandit ...

Silicon Nitride integrated photonic circuits have drawn much attention owing to its ultra-low loss and large Kerr nonlinearity. However, the lack of Pockels effect makes it difficult to be modulated clectro-optically, which posts a major challenge for the ...

This paper presents a comparative study, analyzing the potentials of pulse amplitude modulation (PAM) for implementing next generation high-speed copper wireline links. This comparative study analyzes the sensitivities of PAM2, PAM4 and PAM8 to inter-symbo ...

This paper presents a 32 Gb/s 16-level pulse amplitude modulation (PAM-16) source-series-terminated transmitter (TX) and a receiver (RX) analog front-end (AFE) in 28 nm FDSOI. The 8-way time-interleaved successive-approximation register (SAR) analog-to-dig ...

As an increase of intelligent and self-powered devices is forecasted for our future everyday life, the implementation of energy-autonomous devices that can wirelessly communicate data from sensors is crucial. Even though techniques such as voltage scaling ...

With the advent of intelligent sensor nodes in everyday life, low power aspects of system design become more and more important. Adaptive body biasing is a promising methodology to achieve dynamic adaptation of the tradeoff between performance and energy b ...

Silicon and oxygen are potential light elements in Earth's core because their stronger affinity to metal observed with increasing temperature posits that significant amounts of both can be incorporated into the core. It was proposed that an Fe-Si-O liquid ...

Promising results of state-of-the-art quantum computers fuel a world-wide effort in academic and private research laboratories to scale up the number of qubits and improve their characteristics in large arrays. To meet the scale-up challenge, innovative mi ...

We experimentally demonstrate three-fold wavelength multicasting of a 64-quadrature-amplitude-modulation (QAM), 120-Gbit/s data channel using a microresonator Kerr frequency comb and nonlinear wave mixing. The multicasting is achieved with a data signal an ...

Two distinct limits for deep learning have been derived as the network width h -> infinity, depending on how the weights of the last layer scale with h. In the neural tangent Kernel (NTK) limit, the dynamics becomes linear in the weights and is described b ...

Despite the existence of various neural recording and mapping techniques, there is an open territory for the emergence of novel techniques. The current neural imaging and recording techniques suffer from invasiveness, a time-consuming labeling process, poo ...

The impact of technological advancement became significant and still has an essential role to play in the diagnosis and treatment of diseases. Nowadays, personalized medicine and therapy are on the rise as a consequence of the developed and cheaper medical ...

A Low Power Current-Mode Binary-Tree WTA / LTA Circuit for Kohonen Neural Networks

Chattez avec Graph Search

Nanowatt Acoustic Inference Sensing Exploiting Nonlinear Analog Feature Extraction

Enhanced-performance integrated Resonant Switched-Capacitor and Buck DC-DC converters for application in extreme radiation and magnetic field environments

A 16-Channel Wireless Neural Recording System-on-Chip with CHT Feature Extraction Processor in 65nm CMOS

Nanoimaging of Ultrashort Magnon Emission by Ferromagnetic Grating Couplers at GHz Frequencies

Tessellation and lmprovement of Simplicial Meshes using Neural Networks

Random flip-flop: adding quantum randomness to digital circuits for improved cyber security, artificial intelligence and more

CMOS-Based Readout and Control Electronics for Microgrippers

Characterization and Modeling of Total Ionizing Dose Effects on Nanoscale MOSFETs for Particle Physics Experiments

Asymptotically Optimal Contextual Bandit Algorithm Using Hierarchical Structures

X-Band Aom On Chip

ISI Sensitivity of PAM Signaling for Very High-Speed Short-Reach Copper Links

A 32 Gb/s PAM-16 TX and ADC-Based RX AFE with 2-tap embedded analog FFE in 28 nm FDSOI

Low-Power Design of Digital VLSI Circuits around the Point of First Failure

Adaptive Body Biasing in Strong Body Factor Technologies

Ab Initio Molecular Dynamics Investigation of Molten Fe-Si-O in Earth's Core

Cryogenic MOSFET Modeling for Large-Scale Quantum Computing

Experimental demonstration of three-fold wavelength multicasting of a 64-QAM 120 Gbit/s data channel using a Kerr frequency comb and nonlinear wave mixing

Disentangling feature and lazy training in deep neural networks

Membrane activity detection in cultured cells using phase-sensitive plasmonics

Wireless Power Transfer and Data Communication for Implantable Autonomous Monitoring and Detection of Epilepsy In Vivo