Valores Próprios (IST)

Valores Próprios (IST)

Curso sobre valores próprios e vetores próprios que assenta na análise deste conceito de Álgebra Linear no contexto de transformações lineares, sistemas dinâmicos e outros modelos. No curso serão ainda bordados valores singulares. Neste curso sobre valores próprios (va.p) e vetores próprios (ve.p.) damos especial atenção às várias aplicações deste conceito fundamental de Álgebra Linear na ciência e engenharia.

Começamos por analisar o seu papel nas transformações geométricas, para depois os vermos a explicar a evolução de sistemas dinâmicos que incluem modelos predador-presa e modelos de sobrevivência de uma espécie. Também abordamos alguns modelos simples de mecânica clássica e quântica que usam a linguagem dos va.p. e ve.p. A descrição de uma aplicação moderna do processamento de imagens digitais vai permitir abordar o tópico recente dos valores singulares. A decomposição em valores singulares é um tópico, que apesar de não ser geralmente contemplado nos programas curriculares de uma primeira disciplina de Álgebra Linear, tem muito interesse nas aplicações e revela propriedades algébricas e geométricas fundamentais das matrizes e respetivas transformações lineares.

Do ponto de vista matemático, a abordagem dos va.p. e ve.p. neste curso inclui, para além da descrição do procedimento clássico para os calcular, as questões da diagonalização e diagonalização ortogonal de matrizes e a análise do teorema espetral. Mostramos, ainda, alguns resultados sobre aproximações para va.p. e ve.p. quando as matrizes são de grandes dimensões. No caso de matrizes retangulares, introduzimos o conceito de valores singulares que são uma extensão natural das boas propriedades das matrizes simétricas definidas positivas, chamando a atenção para o seu interesse para qualquer matriz diagonalizável, ou não diagonalizável.
No final deste curso, os participantes deverão estar aptos a:

  • calcular manualmente va.p. e ve.p. próprios para matrizes 2x2 e 3x3;
  • calcular, com recurso a software, va.p. e ve.p. próprios para matrizes mais complicadas;
  • interpretar o significado dos va.p e ve.p. no contexto de transformações lineares, sistemas dinâmicos e formas quadráticas;
  • diagonalizar matrizes, classificar formas quadráticas e usar a decomposição espetral em algumas aplicações;
  • aplicar o método numérico da potência para o cálculo aproximado de va.p. e ve.p. dominantes.

Recommended Readings:
D.C. Lay, S.R. Lay & J.J. McDonald (2016). Linear Algebra and Its Applications (4th Edition). Global Edition. Pearson

Pré-requisitos
Ao nível de conhecimentos em matemática:

  • familiaridade com alguns conceitos básicos de Álgebra Linear: operações matriciais, determinantes, independência linear e bases ortonormais;
  • saber encontrar raízes de polinómios e soluções de equações diferenciais simples;
  • manipular algebricamente números complexos.

Ao nível de software de cálculo numérico e simbólico:

  • saber usar um software adequado, como por exemplo o Mathematica, MATLAB ou Maple.
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