Equação Linear
É toda equação que possui variáveis e apresenta na seguinte forma a1x1 + a2x2 + a3x3 + ...+ anxn = b, em que a1, a2, a3, ....., são os coeficientes reais e o termo independente e representado pelo número real b.
Exemplos:
x + y + z = 20
2x –3y + 5z = 6
4x + 5y – 10z = –3
x – 4y – z = 0
x + y + z = 20
2x –3y + 5z = 6
4x + 5y – 10z = –3
x – 4y – z = 0
Sistema Linear
Um conjunto de pequenas equações lineares com variáveis x1, x2, x3,....,xn formam um sistema linear com p equações e n incógnitas.
Exemplos:
x + y = 3
x – y = 1
Sistema linear com duas equações e duas variáveis.
2x + 5y – 6z = 24
x – y + 10z = 30
Sistema linear com duas equações e três variáveis.
x + 10y – 12z = 120
4x – 2y – 20z = 60
–x + y + 5z = 10
Sistema linear com três equações e três variáveis.
x – y – z + w = 10
2x + 3y + 5z – 2w = 21
4x – 2y – z + w = 16
Sistema linear com três equações e quatro variáveis.
Solução de um sistema linear
Dado o sistema:
x + y = 3
x – y = 1
Dizemos que a solução deste sistema é o par ordenado (2,1), pois ele satisfaz as duas equações do sistema linear. Observe:
x = 2 e y = 1
2 + 1 = 3 3 = 3
2 – 1 = 1 1 = 1
Dado o sistema:
2x + 2y + 2z = 20
2x – 2y + 2z = 8
2x – 2y – 2z = 0
2 + 1 = 3 3 = 3
2 – 1 = 1 1 = 1
Dado o sistema:
2x + 2y + 2z = 20
2x – 2y + 2z = 8
2x – 2y – 2z = 0
Podemos dizer que o trio ordenado (5, 3, 2) é solução do sistema, pois ele satisfaz as três equações do sistema linear. Veja:
2 * 5 + 2 * 3 + 2 * 2 = 20 10 + 6 + 4 = 20 20 = 20
2 * 5 – 2 * 3 + 2 * 2 = 8 10 – 6 + 4 = 8 8 = 8
2 * 5 – 2 * 3 – 2 * 2 = 0 10 – 6 – 4 = 0 0 = 0
Classificação de um sistema linear
Todo sistema linear é classificado de acordo com o número de soluções apresentadas por ele.
SPD – Sistema Possível e Determinado – possui apenas uma solução.
SPI – Sistema Possível e Indeterminado – possui infinitas soluções.
SI – Sistema Impossível – não possui solução.
Associando um sistema linear a uma matriz
Um sistema linear pode estar associado a uma matriz, os seus coeficientes ocuparão as linhas e as colunas da matriz, respectivamente. Veja exemplo 1:
O sistema:
x + y = 3
x – y = 1
pode ser representado por duas matrizes, uma completa e outra incompleta.
Matriz completa
1 | 1 | 3 |
1 | -1 | 1 |
Matriz incompleta
1 | 1 |
1 | -1 |
Exemplo 2
x + 10y – 12z = 120
4x – 2y – 20z = 60
–x + y + 5z = 10
Matriz completa
1 | 10 | -12 | 120 |
4 | -2 | -20 | 60 |
-1 | 1 | 5 | 10 |
Matriz incompleta
1 | 10 | -12 |
4 | -2 | -20 |
-1 | 1 | 5 |
Obs.: O sistema também pode possuir uma representação matricial. Observe o sistema de equações lineares:
x + 10y – 12z = 120
4x – 2y – 20z = 60
–x + y + 5z = 10
Equação matricial do sistema:
![](data:image/png;base64,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)
x + 10y – 12z = 120
4x – 2y – 20z = 60
–x + y + 5z = 10
Equação matricial do sistema:
Segue abaixo uma lista de exercícios resolvidos sobre SISTEMAS LINEARES.
Nenhum comentário:
Postar um comentário