public static Vector2 FindMin(Vector2 x0, double eps)
{
double alpha;
double f;
Vector2 grad;
int i = 0;
Vector2 x;
do
{
//Устанавливаем максимальное значение alpha
alpha = alphaMax;
//Вычисляем градиент в x_k
grad = Rosenbrock.Gradient(x0);
//Проверяем условие Армихо
do
{
i++;
alpha *= 0.75;
x = x0 - alpha * grad;
f = -(Rosenbrock.F(x) - Rosenbrock.F(x0)) / (alpha * grad.Norm * grad.Norm);
} while (!((delta1 <= f) && (f <= delta2)));
x = x0.Copy();
x0 -= alpha * Rosenbrock.Gradient(x0);
}while(grad.Norm > eps);
Console.WriteLine("Iterations:\t{0}", i);
return(x);
}
public static Vector2 FindMin(Vector2 x, double EPS)
{
int i = 0;
double alpha;
Vector2 grad = Rosenbrock.Gradient(x);
Vector2 d = -1 * Rosenbrock.Gradient(x);
double prevGradSquare;
do
{
i++;
prevGradSquare = grad.Norm * grad.Norm;
alpha = Rosenbrock.GoldenSearch(x, d);
x += alpha * d;
grad = Rosenbrock.Gradient(x);
if (i % 2 == 0)
{
d = -1 * grad;
}
else
{
double beta = grad.Norm * grad.Norm / prevGradSquare;
d = beta * d - grad;
}
} while(d.Norm > EPS);
Console.WriteLine("Iterations:\t{0}", i);
return(x);
}
public static Vector2 FindMin(Vector2 p, double eps)
{
Vector2 p0;
double[,] H;
Vector2 grad;
do
{
p0 = p.Copy();
H = Newton.InverseHessian(p0);
grad = Rosenbrock.Gradient(p0);
p -= (H * grad);
} while ((p - p0).Norm > eps);
return(p);
}
public static Vector2 FindMin(Vector2 point, double EPS)
{
Vector2 delta = new Vector2(0.1, 0.1);
Vector2 df;
Vector2 dfPrev = new Vector2(0, 0);
int k = 0;
do
{
k++;
df = Rosenbrock.Gradient(point);
for (int i = 0; i < 2; i++)
{
double product = df[i] * dfPrev[i];
if (product > 0)
{
delta[i] = Math.Min(delta[i] * etaPlus_, deltaMax_);
point[i] -= Math.Sign(df[i]) * delta[i];
dfPrev[i] = df[i];
}
else if (product < 0)
{
delta[i] = Math.Max(delta[i] * etaMinus_, deltaMin_);
dfPrev[i] = 0;
}
else
{
point[i] -= Math.Sign(df[i]) * delta[i];
dfPrev[i] = df[i];
}
}
} while (df.Norm > 1e-7);
Console.WriteLine("Iterations:\t{0}", k);
return(point);
}
