Galerieelemente in der Kategorie Math
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Fundamentals of Signal Enhancement and Array Signal Processing Solution Manual (section 10)
section 10
lidor malul
![2022年第七届数维杯数学建模](https://writelatex.s3.amazonaws.com/published_ver/24188.jpeg?X-Amz-Expires=14400&X-Amz-Date=20240630T212116Z&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAWJBOALPNFPV7PVH5/20240630/us-east-1/s3/aws4_request&X-Amz-SignedHeaders=host&X-Amz-Signature=555871c67579d8cc85c945fcdc3d1dc7cb3b2906cd43726d5a8ac4439c2b48f9)
2022年第七届数维杯数学建模
2022年第七届数维杯数学建模
维杯数学建模组委会
![PUC-Rio Optimization 2019.1](https://writelatex.s3.amazonaws.com/published_ver/9628.jpeg?X-Amz-Expires=14400&X-Amz-Date=20240630T212116Z&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAWJBOALPNFPV7PVH5/20240630/us-east-1/s3/aws4_request&X-Amz-SignedHeaders=host&X-Amz-Signature=e7b507086a80a9b0d01c38091a74056a577911626f99f63da7e15dad00c22d81)
PUC-Rio Optimization 2019.1
Template to use in PUC-Rio Optimization course 2019.1
Guilherme Bodin and Joaquim Garcia
![TIPE brachistochrone](https://writelatex.s3.amazonaws.com/published_ver/8543.jpeg?X-Amz-Expires=14400&X-Amz-Date=20240630T212116Z&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAWJBOALPNFPV7PVH5/20240630/us-east-1/s3/aws4_request&X-Amz-SignedHeaders=host&X-Amz-Signature=279baf427868d45a19fee7c52b974a26767624ea6ac0f024217a8ce887c96727)
TIPE brachistochrone
On découpe ce document complexe en plusieurs sous-fichiers séparés.
Cela permettra notamment de réarranger les transparents facilement
lors de l'élaboration du document.
louis
![Logarithms](https://writelatex.s3.amazonaws.com/published_ver/1902.jpeg?X-Amz-Expires=14400&X-Amz-Date=20240630T212116Z&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAWJBOALPNFPV7PVH5/20240630/us-east-1/s3/aws4_request&X-Amz-SignedHeaders=host&X-Amz-Signature=b1b39524e9baa407714cda0f6a2f3aef12f3bb6f7e28a065af20161ef8c890a8)
Logarithms
My guide to logarithms.
Rithwik Palivela
![Math 53 Homework template](https://writelatex.s3.amazonaws.com/published_ver/7950.jpeg?X-Amz-Expires=14400&X-Amz-Date=20240630T212116Z&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAWJBOALPNFPV7PVH5/20240630/us-east-1/s3/aws4_request&X-Amz-SignedHeaders=host&X-Amz-Signature=d2774c9b8708be64664a460b164c07c40ee6a138e4a8afcc93ef6df5f93a625d)
Math 53 Homework template
For math 53 homework
Jupiter Zhu
![Barebones PSET Template](https://writelatex.s3.amazonaws.com/published_ver/1884.jpeg?X-Amz-Expires=14400&X-Amz-Date=20240630T212116Z&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAWJBOALPNFPV7PVH5/20240630/us-east-1/s3/aws4_request&X-Amz-SignedHeaders=host&X-Amz-Signature=ea7b9efec5290d4ea32dfe868cacdac8760012bdd225676e76cf9a599aff7a93)
Barebones PSET Template
A (minimal) template for problem sets and solutions using the exam document class
Organization:
Define new commands, macros, etc. in macros.tex
Anything that you would put before \begin{document} should go in prelude.tex
Jack Gallagher
![Plantilla de Trabajo Prácico UTN FRRo](https://writelatex.s3.amazonaws.com/published_ver/8271.jpeg?X-Amz-Expires=14400&X-Amz-Date=20240630T212116Z&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAWJBOALPNFPV7PVH5/20240630/us-east-1/s3/aws4_request&X-Amz-SignedHeaders=host&X-Amz-Signature=c800a30e1a40d8f1314fb701f4152ea1018cbbc02ce471df7d4a6552a179b21f)
Plantilla de Trabajo Prácico UTN FRRo
Esta es una plantilla utilizada para la presentación de trabajos prácticos, cuenta con elementos predefinidos y distintas secciones. Originalmente fue diseñana para la cátedra de Simulación de Ingeniería en Sistemas pero se puede utilizar para cualquier otra cátedra
Ezequiel Leonardo Castaño
![Robot localization in a mapped environment using Adaptive Monte Carlo algorithm](https://writelatex.s3.amazonaws.com/published_ver/8266.jpeg?X-Amz-Expires=14400&X-Amz-Date=20240630T212116Z&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAWJBOALPNFPV7PVH5/20240630/us-east-1/s3/aws4_request&X-Amz-SignedHeaders=host&X-Amz-Signature=d91c10651fb140977a924d04d7052c4c509bffaaf51eb3ba2a00121affbde285)
Robot localization in a mapped environment using Adaptive Monte Carlo algorithm
Localization is the challenge of determining the robot's pose in a mapped environment. This is done by implementing a probabilistic algorithm to filter noisy sensor measurements and track the robot's position and orientation. This paper focuses on localizing a robot in a known mapped environment using Adaptive Monte Carlo Localization or Particle Filters method and send it to a goal state. ROS, Gazebo and RViz were used as the tools of the trade to simulate the environment and programming two robots for performing localization.
Sagarnil Das