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Lyapunov Characteristic Number -- from Wolfram MathWorld

Given a Lyapunov characteristic exponent sigma_i, the corresponding Lyapunov characteristic number lambda_i is defined as lambda_i=e^(sigma_i). (1) For an n-dimensional linear map, X_(n+1)=MX_n. (2) The Lyapunov characteristic numbers lambda_1, ..., lambda_n are the eigenvalues of the map matrix. For an arbitrary map x_(n+1)=f_1(x_n,y_n) (3) y_(n+1)=f_2(x_n,y_n), (4) the Lyapunov numbers are the eigenvalues of the limit ...



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Lyapunov Characteristic Number -- from Wolfram MathWorld

https://mathworld.wolfram.com/LyapunovCharacteristicNumber.html

Given a Lyapunov characteristic exponent sigma_i, the corresponding Lyapunov characteristic number lambda_i is defined as lambda_i=e^(sigma_i). (1) For an n-dimensional linear map, X_(n+1)=MX_n. (2) The Lyapunov characteristic numbers lambda_1, ..., lambda_n are the eigenvalues of the map matrix. For an arbitrary map x_(n+1)=f_1(x_n,y_n) (3) y_(n+1)=f_2(x_n,y_n), (4) the Lyapunov numbers are the eigenvalues of the limit ...



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https://mathworld.wolfram.com/LyapunovCharacteristicNumber.html

Lyapunov Characteristic Number -- from Wolfram MathWorld

Given a Lyapunov characteristic exponent sigma_i, the corresponding Lyapunov characteristic number lambda_i is defined as lambda_i=e^(sigma_i). (1) For an n-dimensional linear map, X_(n+1)=MX_n. (2) The Lyapunov characteristic numbers lambda_1, ..., lambda_n are the eigenvalues of the map matrix. For an arbitrary map x_(n+1)=f_1(x_n,y_n) (3) y_(n+1)=f_2(x_n,y_n), (4) the Lyapunov numbers are the eigenvalues of the limit ...

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      Lyapunov Characteristic Number -- from Wolfram MathWorld
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      Given a Lyapunov characteristic exponent sigma_i, the corresponding Lyapunov characteristic number lambda_i is defined as lambda_i=e^(sigma_i). (1) For an n-dimensional linear map, X_(n+1)=MX_n. (2) The Lyapunov characteristic numbers lambda_1, ..., lambda_n are the eigenvalues of the map matrix. For an arbitrary map x_(n+1)=f_1(x_n,y_n) (3) y_(n+1)=f_2(x_n,y_n), (4) the Lyapunov numbers are the eigenvalues of the limit ...
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      Given a Lyapunov characteristic exponent sigma_i, the corresponding Lyapunov characteristic number lambda_i is defined as lambda_i=e^(sigma_i). (1) For an n-dimensional linear map, X_(n+1)=MX_n. (2) The Lyapunov characteristic numbers lambda_1, ..., lambda_n are the eigenvalues of the map matrix. For an arbitrary map x_(n+1)=f_1(x_n,y_n) (3) y_(n+1)=f_2(x_n,y_n), (4) the Lyapunov numbers are the eigenvalues of the limit ...

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      Given a Lyapunov characteristic exponent sigma_i, the corresponding Lyapunov characteristic number lambda_i is defined as lambda_i=e^(sigma_i). (1) For an n-dimensional linear map, X_(n+1)=MX_n. (2) The Lyapunov characteristic numbers lambda_1, ..., lambda_n are the eigenvalues of the map matrix. For an arbitrary map x_(n+1)=f_1(x_n,y_n) (3) y_(n+1)=f_2(x_n,y_n), (4) the Lyapunov numbers are the eigenvalues of the limit ...

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      Given a Lyapunov characteristic exponent sigma_i, the corresponding Lyapunov characteristic number lambda_i is defined as lambda_i=e^(sigma_i). (1) For an n-dimensional linear map, X_(n+1)=MX_n. (2) The Lyapunov characteristic numbers lambda_1, ..., lambda_n are the eigenvalues of the map matrix. For an arbitrary map x_(n+1)=f_1(x_n,y_n) (3) y_(n+1)=f_2(x_n,y_n), (4) the Lyapunov numbers are the eigenvalues of the limit ...
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