A New FFT-Based Algorithm for Secondary Code Acquisition for Galileo Signals

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Navigation of drones is predominantly based on sensor fusion algorithms. Most of these algorithms make use of some form of Bayesian filtering with a majority employing an Extended Kalman Filter (EKF), wherein inertial measurements are fused with a Global N ...

This article investigates the performance and accuracy of continuous Real-Time Kinematic (RTK) Global Navigation Satellite System (GNSS) position tracking for hydromorphological surveys, based on a comprehensive river restoration monitoring campaign. The a ...

We introduce an algorithm to reconstruct a mesh from discrete samples of a shape's Signed Distance Function (SDF). A simple geometric reinterpretation of the SDF lets us formulate the problem through a point cloud, from which a surface can be extracted wit ...

This paper offers a new algorithm to efficiently optimize scheduling decisions for dial-a-ride problems (DARPs), including problem variants considering electric and autonomous vehicles (e-ADARPs). The scheduling heuristic, based on linear programming theor ...

In this paper, we study sampling from a posterior derived from a neural network. We propose a new probabilistic model consisting of adding noise at every pre- and post-activation in the network, arguing that the resulting posterior can be sampled using an ...

We propose an adaptive quantum algorithm to prepare accurate variational time evolved wave functions. The method is based on the projected variational quantum dynamics (pVQD) algorithm, that performs a global optimization with linear scaling in the number ...

Graph neural networks (GNNs) have demonstrated promising performance across various chemistry-related tasks. However, conventional graphs only model the pairwise connectivity in molecules, failing to adequately represent higher order connections, such as m ...

The success of drone missions is incumbent on an accurate determination of the drone pose and velocity, which are collectively estimated by fusing iner- tial measurement unit and global navigation satellite system (GNSS) mea- surements. However, during a G ...

Finding cycles in directed graphs enables important applications in various domains such as finance, biology, chemistry, and network science. However, as the size of graph datasets continues to grow, it becomes increasingly difficult to discover cycles wit ...

Non-convex constrained optimization problems have become a powerful framework for modeling a wide range of machine learning problems, with applications in k-means clustering, large- scale semidefinite programs (SDPs), and various other tasks. As the perfor ...

The ionosphere can be perturbed by solar and geomagnetic activity, earthquakes, thunderstorms, etc. In particular, electromagnetic pulses produced by thunderstorms can generate wave structures in the ionospheric plasma, which are known as atmospheric gravi ...

Collaborative learning algorithms, such as distributed SGD (or D-SGD), are prone to faulty machines that may deviate from their prescribed algorithm because of software or hardware bugs, poisoned data or malicious behaviors. While many solutions have been ...

A force-feedback surface that creates and modulates distinctive profile and stiffnessto interact with a user in contact thereto, the surface being functionally independentto be used as a single module but can be customized to extend the application indiver ...

An integer linear program is a problem of the form max{c^T x : Ax=b, x >= 0, x integer}, where A is in Z^(n x m), b in Z^m, and c in Z^n. Solving an integer linear program is NP-hard in general, but there are several assumptions for which it becomes fixed ...

The advent of comprehensive synaptic wiring diagrams of large neural circuits has created the field of connectomics and given rise to a number of open research questions. One such question is whether it is possible to reconstruct the information stored in ...

Federated learning is a semi-distributed algorithm, where a server communicates with multiple dispersed clients to learn a global model. The federated architecture is not robust and is sensitive to communication and computational overloads due to its one-m ...

An important advantage of optical signal processing is the possibility of performing various operations in parallel. Among the techniques proposed for parallel optical signal processing, frequency division multiplexing (FDM) is a well-known approach, in wh ...

This work presents a graph neural network (GNN) framework for solving the maximum independent set (MIS) problem, inspired by dynamic programming (DP). Specifically, given a graph, we propose a DP-like recursive algorithm based on GNNs that firstly construc ...

In this thesis, we give new approximation algorithms for some NP-hard problems arising in resource allocation and network design. As a resource allocation problem, we study the Santa Claus problem (also known as the MaxMin Fair Allocation problem) in which ...

Two prominent categories for achieving coordinated multirobot displacement are flocking and navigation in formation. Both categories have their own body of literature and characteristics, including their respective advantages and disadvantages. While typic ...

A New FFT-Based Algorithm for Secondary Code Acquisition for Galileo Signals

Chattez avec Graph Search

VDMNav: Software Architecture for Aerodynamically Constrained Navigation on Small Fixed-Wing Drones

Performance and accuracy of cross‐section tracking methods for hydromorphological habitat assessment in wadable rivers with sparse canopy conditions

Reach For the Arcs: Reconstructing Surfaces from SDFs via Tangent Points

A ride time-oriented scheduling algorithm for dial-a-ride problems

Gibbs sampling the posterior of neural networks

Adaptive projected variational quantum dynamics

Molecular hypergraph neural networks

Identifying aerodynamics of small fixed-wing drones using inertial measurements for model-based navigation

Fast Parallel Algorithms for Enumeration of Simple, Temporal, and Hop-Constrained Cycles

Augmented Lagrangian Methods for Provable and Scalable Machine Learning

Ionospheric Variations Induced by Thunderstorms in the Central Region of Argentina during the RELAMPAGO–CACTI Campaign

Robust Collaborative Learning with Linear Gradient Overhead

Device and system as human interactive surface

Results on Sparse Integer Programming and Geometric Independent Sets

Bayesian reconstruction of memories stored in neural networks from their connectivity

Privatized graph federated learning

Topological MIMO Optical Signal Processing

Maximum Independent Set: Self-Training through Dynamic Programming

Approximation Algorithms for Allocation and Network Design

Hybrid Flock - Formation Control Algorithms