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Sangdon Lee
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Just out of curiosity, do we need some kind of precision control on numerical computation because I see the x[n] values are very close to zero (e.g., between 2.0x10^-18 and -1.5x10^-18)?
Thanks for the great analysis and information. The concept of dimensionality is really good to me. I would like to see PCA/FA/SEM with various rotation options in Mathematica. In general, PCA is a first step to understand the latent structure...
Several typing errors are removed. I used the ParametricNDSolve, rather than ParametricNDSolveValue. We = 0.4; alpha = 0.9; beta = 0.2; phi = 0.7; P = -1.3; Br = 0.1; K1 = We^2*(1 - alpha^2); K2 = phi*K1; system = { ...
You need to specify where to find Python: RegisterExternalEvaluator[ "Python", "C:\\bin\\Anaconda3\\python.EXE"] Register a Python-Numpy library: RegisterExternalEvaluator[ "Python-NumPy", ...
I used the following prompts : > Analyze the following Mathematica codes very carefully and create an artistic rendering of how the result would look like in 3D: ComplexPlot[ZTransform[n^2*UnitStep[n] - n^2*UnitStep[n - 10], n, z], ...
May be the "NCAlgebra" package? https://mathweb.ucsd.edu/~ncalg/ Section 4.7 from: https://mathweb.ucsd.edu/~ncalg/DOCUMENTATION/index.html#MostBasicCommands
I suspect that different scaling is applied to standadizae variables in MMA, which confuses me much. The usual standardization indicates that variables have average values of zero and standard deviations of one for variables. However, MMA may apply...
I recently found that the MXNET was retired as of Sep. 2023 and it is no longer actively developed as indicated from its website and Wikipedia. Mathematica uses MxNet as the backend for neural networks. - [Wikipedia][1] - [Apache][2] [1]:...
Thank you for clarification. Could you please provide few references? I am not aware of this biased estimator for the variance.
1. w0 is not defined. 2. The "x" in u[x],v[x],w[x] and z[x] is an independent parameter (e.g., "x" is similar to "t" in ODE) but you again used the "x" as a state or dependent variable (i.e., x[t]:= Log[1 + t]/Log[10]). Thus x in u[x] and x in...