Results 51 to 60 of about 541,388 (266)
Advanced Electronic Materials, EarlyView.This study presents an ECRAM‐based physical reservoir computing system for real‐time electrocardiogram arrhythmia detection. By optimizing electrolyte ionic conductivity and channel ionic diffusivity, it achieves including non‐linear dynamics, millisecond‐scale tunable retention, low‐power operation, and minimal variation.
Kyumin Lee +3 more
wiley +1 more source
Deep Task-Based Quantization [PDF]
arXiv, 2019 Quantizers play a critical role in digital signal processing systems. Recent works have shown that the performance of quantization systems acquiring multiple analog signals using scalar analog-to-digital converters (ADCs) can be significantly improved by properly processing the analog signals prior to quantization.
arxiv
Low-Complexity Vector Quantized Compressed Sensing via Deep Neural Networks [PDF]
arXiv, 2020 Sparse signals, encountered in many wireless and signal acquisition applications, can be acquired via compressed sensing (CS) to reduce computations and transmissions, crucial for resource-limited devices, e.g., wireless sensors. Since the information signals are often continuous-valued, digital communication of compressive measurements requires ...
arxiv
Variational Bayesian algorithm for quantized compressed sensing [PDF]
, 2012 Compressed sensing (CS) is on recovery of high dimensional signals from their low dimensional linear measurements under a sparsity prior and digital quantization of the measurement data is inevitable in practical implementation of CS algorithms. In the existing literature, the quantization error is modeled typically as additive noise and the multi-bit ...
arxiv +1 more source
Advanced Intelligent Systems, EarlyView.This study investigates the device specifications required for neural network training using analog resistive cross‐point arrays with the training algorithms. By demonstrating the robustness against non‐ideal update characteristics with these algorithms, it quantitatively shows how hardware‐aware training can relax device specifications.
Jinho Byun +5 more
wiley +1 more source
Deep Learning Methods in Soft Robotics: Architectures and Applications
Advanced Intelligent Systems, EarlyView.Soft robotics has seen intense research over the past two decades and offers a promising approach for future robotic applications. However, standard industrial methods may be challenging to apply to soft robots. Recent advances in deep learning provide powerful tools to analyze and design complex soft machines that can operate in unstructured ...
Tomáš Čakurda +3 more
wiley +1 more source
Novel Near-Optimal Scalar Quantizers with Exponential Decay Rate and Global Convergence [PDF]
arXiv, 2018 Many modern distributed real-time signal sensing/monitoring systems require quantization for efficient signal representation. These distributed sensors often have inherent computational and energy limitations. Motivated by this concern, we propose a novel quantization scheme called approximate Lloyd-Max that is nearly-optimal. Assuming a continuous and
arxiv
Implementation of a Biologically Inspired Responsive Joint Attention System for a Social Robot
Advanced Intelligent Systems, EarlyView.This work introduces a responsive joint attention system in the social robot Mini, enabling dynamic, human‐like responses based on the user's head, body, and gaze. The system enhances user engagement and robot responsiveness. An experiment reveals significant improvements in social presence when the system is active, validating its effectiveness in ...
Jesús García‐Martínez +4 more
wiley +1 more source
Medical Image Hybrid Watermark Algorithm Based on Frequency Domain Processing and Inception v3
Advanced Intelligent Systems, EarlyView.Frequency domain processing and Inceptionv3 method is used in this article for digital image watermarking of medical images. The algorithm extracts feature vectors from medical images using discrete wavelet transform and discrete cosine transform, enhancing the robustness of the image watermark With the widespread use of digital medical images in ...
Yu Fan +4 more
wiley +1 more source
Taking the edge off quantization: projected back projection in dithered compressive sensing [PDF]
arXiv, 2018 Quantized compressive sensing (QCS) deals with the problem of representing compressive signal measurements with finite precision representation, i.e., a mandatory process in any practical sensor design. To characterize the signal reconstruction quality in this framework, most of the existing theoretical analyses lie heavily on the quantization of sub ...
arxiv