benchmarkfcns.periodic¶
- benchmarkfcns.periodic(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 Periodic function. SCORES = periodic(X) computes the value of the Periodic function at point X. periodic accepts a matrix of size M-by-N 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: 0.9
Location of global minimum: (0, 0, …, 0)
Number of dimensions: n
Recommended domain: [-10, 10]^n
Number of local minima: many
Number of global minima: 1
Convexity: non-convex
Separability: separable
Modality: multimodal
Symmetry: symmetric
Differentiable: Yes
For more information, please visit: benchmarkfcns.info/doc/periodicfcn
Mathematical Definition
Visualization