Enhance & Explore: an Adaptive Algorithm to Maximize the Utility of Wireless Networks

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This thesis focuses on two selected learning problems: 1) statistical inference on graphs models, and, 2) gradient descent on neural networks, with the common objective of defining and analysing the measures that characterize the fundamental limits. In th ...

One challenge in designing RF wireless bioelectronic devices is the impact of the interaction between electromagnetic waves and host body tissues on far-field wireless performance. In this paper, we investigate a peculiar phenomenon of implantable RF wirel ...

Wireless data communication could improve the performance and reliability of biomedical implants used in fundamental neuroscience research by removing infection-prone transcutaneous cabling. The small size of common research animals like mice and rodents, ...

Modern programs are monolithic, combining code of varied provenance without isolation, all the while running on network-connected devices. A vulnerability in any component may compromise code and data of all other components. Compartmentalization separates ...

The CA1 region of the hippocampus is one of the most studied regions of the rodent brain, thought to play an important role in cognitive functions such as memory and spatial navigation. Despite a wealth of experimental data on its structure and function, i ...

Network neutrality is important for users, content providers, policymakers, and regulators interested in understanding how network providers differentiate performance. When determining whether a network differentiates against certain traffic, it is importa ...

Deep neural networks trained on physical losses are emerging as promising surrogates for nonlinear numerical solvers. These tools can predict solutions to Maxwell's equations and compute gradients of output fields with respect to the material and geometric ...

Human voluntary movement stems from the coordinated activations in space and time of many musculoskeletal segments. However, the current methodological approaches to study human movement are still limited to the evaluation of the synergies among a few body ...

Signalized intersections are a fundamental part of urban networks. Their understanding is crucial to identify congestion patterns, queues, delays, and safety issues in local and network level. In this work, we analyze multimodal vehicle trajectories and pr ...

The purpose of this research has a background in the market for Internet of Things (IoT)devices and wireless sensor networks. The Market Forecast predicts the connection of a trillion"things" by 2025. The global smart sensor market size trend grows from US ...

Enhance & Explore: an Adaptive Algorithm to Maximize the Utility of Wireless Networks

Chattez avec Graph Search

Fundamental Limits in Statistical Learning Problems: Block Models and Neural Networks

Radiation Patterns of RF Wireless Devices Implanted in Small Animals: Unexpected Deformations Due to Body Resonance

Radiation Performance of Antennas Implanted in Small Animals for Neuroengineering

SecureCells: A Secure Compartmentalized Architecture

Community-based reconstruction and simulation of a full-scale model of region CA1 of rat hippocampus

Localizing Traffic Differentiation

Predicting nonlinear optical scattering with physics-driven neural networks

The kinectome: A comprehensive kinematic map of human motion in health and disease

An automatized signal timing detection at signalized intersections with detailed vehicle trajectory data

Strategies, Techniques and Systems for powering low-maintenance and battery-free devices through Energy Harvesting and Wireless Power Transfer