benchmarkfcns.brent¶
- benchmarkfcns.brent(arg0: Annotated[numpy.typing.NDArray[numpy.float64], '[m, n]', 'flags.c_contiguous']) Annotated[numpy.typing.NDArray[numpy.float64], '[m, 1]']¶
Computes the value of the Brent function. SCORES = brent(X) computes the value of the Brent function at point X. brent accepts a matrix of size M-by-2 and returns a vector SCORES of size M-by-1 in which each row contains the function value for the corresponding row of X. Properties:
Global minimum: 0
Location of global minimum: (-10, -10)
Number of dimensions: 2
Recommended domain: [-10, 10]^2 or [-20, 0]^2
Number of local minima: 1
Number of global minima: 1
Convexity: non-convex
Separability: non-separable
Modality: unimodal
Differentiable: Yes
For more information, please visit: benchmarkfcns.info/doc/brentfcn
Mathematical Definition
Visualization