The only difference is that each nonlinear neuron in the hidden layer has a Gaussian RBF defined as, where is the Euclidean norm between the input vector, x i, and the center vector, c k, and h k is the bandwidth of the Gaussian RBF.
The shape factor is defined as the norm of the major Fourier component of the periodic wall profile.
The space W 0 m, x E M ( Q ) is defined as the (norm) closure in Wm,xE M (Q) of D.
In the literature, the accuracy metric has been studied widely through the position error, defined as the norm of the difference between the estimated and the true position [1, 6].
From [20], we know that ∥ f ∥ B M O A = | f ( 0 ) | + sup a ∈ D ∥ f ∘ φ a − f ( a ) ∥ H p < ∞. can be defined as a norm of B M O A space.
That is, if we represent the total number of pixels in one SCD as npSum, then in individually normalizing method, the normalized SCD is defined as: s norm 2 = n p 1 npSum, n p 2 npSum, …, n p i npSum, …, n p 60 npSum.
Therefore, normalized reflectance defined as R norm ≡ Reflected power density Incident power density (8) Figure 4 Plots of the reflectance spectrum for the (a) cylinder- (b) circular-cone-, (c) and square-pyramid-shaped Si 3 N 4 SWS with incident angles of 0°, 15°, 30°, 45°, and 60°.
For the minimum exposure path, to quantitatively analyze the simplifying efficacy of TGSARWI algorithm to MEP problem, the reduction ratio r is defined as the norm ratio of sub-network G1 formed by n h connected paths to the original grid network G: r=frac{leftVert {G}_1rightVert }{leftVert GrightVert }=frac{leftVert {G}_1rightVert }{mtimes n} (14).
The space W 0 1 E M is defined as the (norm) closure of the Schwartz space D in W1E M and the space W 0 1 L M as the σ ( ∏ L M, ∏ E M ¯ ) closure of D in W1L M. We say that u n converges to u for the modular convergence in W1L M if for some λ > 0, ∫ Ω M D α u n - D α u λ d x → 0 for all |α| ≤ 1.
Motivation to comply with perceived expectations of others is defined as subjective norm within the theory of planned behaviour [ 11, 12].
