C 代码 演示了缩减或截断的计算 奇异值分解 （SVD）.rar

02 September 2018 09:08:57 AM SVD_TRUNCATED C version Demonstrate the use of the truncated or economy-size Singular Value Decomposition (SVD) for cases where the sizes of M and N are very different. SVD_TRUNCATED_U_TEST M = 4 N = 3 A: Col: 0 1 2 Row 0: 0.218418 0.415307 0.043829 1: 0.956318 0.066119 0.633966 2: 0.829509 0.257578 0.061727 3: 0.561695 0.109957 0.449539 UN: Col: 0 1 2 Row 0: -0.183175 -0.646219 -0.706139 1: -0.712493 0.427285 -0.029831 2: -0.507765 -0.582870 0.611171 3: -0.448303 0.245135 -0.356298 SN: Col: 0 1 2 Row 0: 1.586180 0.000000 0.000000 1: 0.000000 0.488342 0.000000 2: 0.000000 0.000000 0.276424 V: Col: 0 1 2 Row 0: -0.879083 -0.160400 0.448871 1: -0.191193 -0.743962 -0.640286 2: -0.436645 0.648685 -0.623337 Maximum error |A - U*S*V'| = 3.33067e-16 Recomputed A = U * S * V': Col: 0 1 2 Row 0: 0.218418 0.415307 0.043829 1: 0.956318 0.066119 0.633966 2: 0.829509 0.257578 0.061727 3: 0.561695 0.109957 0.449539 SVD_TRUNCATED_V_TEST M = 3 N = 4 A: Col: 0 1 2 3 Row 0: 0.218418 0.561695 0.257578 0.633966 1: 0.956318 0.415307 0.109957 0.061727 2: 0.829509 0.066119 0.043829 0.449539 U: Col: 0 1 2 Row 0: -0.458728 -0.880639 -0.118507 1: -0.658087 0.426317 -0.620626 2: -0.597068 0.206710 0.775100 SM: Col: 0 1 2 Row 0: 1.494101 0.000000 0.000000 1: 0.000000 0.681157 0.000000 2: 0.000000 0.000000 0.366801 VM: Col: 0 1 2 Row 0: -0.819763 0.567879 0.064213 1: -0.381802 -0.446198 -0.744454 2: -0.145029 -0.250892 -0.176649 3: -0.401476 -0.644573 0.640671 Maximum error |A - U*S*V'| = 1.11022e-15 Recomputed A = U * S * V': Col: 0 1 2 3 Row 0: 0.218418 0.561695 0.257578 0.633966 1: 0.956318 0.415307 0.109957 0.061727 2: 0.829509 0.066119 0.043829 0.449539 SVD_TRUNCATED Normal end of execution. 02 September 2018 09:08:57 AM