# Dc algorithms in nonconvex quadratic programming and applications in data clustering

Example 4.6 Let n; m; k; A be as in Example 4.1, i.e., n = 2, m = 3, k = 2, A = fa1; a2; a3g, where a1 = (0; 0), a2 = (1; 0), a3 = (0; 1). Let γ1 = 0:3, γ2 = 0:3 and γ3 = 3: The implementation of Algorithm 4.6 begins with putting x¯1 = a0 and setting ‘ = 1. Since ‘ < k, we apply Procedure 4.10 to find an approximate solution ^ x = (^ x1; : : : ; x^‘+1) of problem (4.8). By the results in Example 4.1, we have A¯3 = A¯2 = A¯1 = A = fa1; a2; a3g: Next, we apply Procedure 4.10 to (4.8) with initial points from Ω = f(¯ x1; a1); (¯ x1; a2); (¯ x1; a3)g to find Ae4. Since the calculation of A~4 coincides with that of Ab5 in Example 4.3, one gets 142 trang | Chia sẻ: tueminh09 | Ngày: 25/01/2022 | Lượt xem: 191 | Lượt tải: 0
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