The model consists of two systems, a climate control system and an electrical system. This allows for examination of the loading effects of the climate control system on the car s electrical system.
Dijkstra算法求最短路徑(C#版) using system
using system.Collections
using system.Text
namespace Greedy
{
class Marx
{
private int[] distance
private int row
private ArrayList ways = new ArrayList()
public Marx(int n,params int[] d)
{
this.row = n
distance = new int[row * row]
for (int i = 0 i < row * row i++)
{
this.distance[i] = d[i]
We present a particle filter construction for a system that exhibits
time-scale separation. The separation of time-scales allows two simplifications
that we exploit: i) The use of the averaging principle for the
dimensional reduction of the system needed to solve for each particle
and ii) the factorization of the transition probability which allows the
Rao-Blackwellization of the filtering step. Both simplifications can be
implemented using the coarse projective integration framework. The
resulting particle filter is faster and has smaller variance than the particle
filter based on the original system. The convergence of the new
particle filter to the analytical filter for the original system is proved
and some numerical results are provided.
