Search results
Results from the WOW.Com Content Network
Some features of convolution are similar to cross-correlation: for real-valued functions, of a continuous or discrete variable, convolution () differs from cross-correlation only in that either () or () is reflected about the y-axis in convolution; thus it is a cross-correlation of () and (), or () and ().
The two methods are also compared in Figure 3, created by Matlab simulation. The contours are lines of constant ratio of the times it takes to perform both methods. When the overlap-add method is faster, the ratio exceeds 1, and ratios as high as 3 are seen. Fig 3: Gain of the overlap-add method compared to a single, large circular convolution.
the solution of the initial-value problem = is the convolution (). Through the superposition principle , given a linear ordinary differential equation (ODE), L y = f {\displaystyle Ly=f} , one can first solve L G = δ s {\displaystyle LG=\delta _{s}} , for each s , and realizing that, since the source is a sum of delta functions , the solution ...
If carried out naively, this is quite expensive. First, the field lines have to be computed using a numerical method for solving ordinary differential equations, like a Runge–Kutta method, and then for each pixel the convolution along a field line segment has to be calculated. The final image will normally be colored in some way.
Fig 2: A graph of the values of N (an integer power of 2) that minimize the cost function ( +) + When the DFT and IDFT are implemented by the FFT algorithm, the pseudocode above requires about N (log 2 (N) + 1) complex multiplications for the FFT, product of arrays, and IFFT.
Another examples is the Weisfeiler-Leman graph kernel [9] which computes multiple rounds of the Weisfeiler-Leman algorithm and then computes the similarity of two graphs as the inner product of the histogram vectors of both graphs. In those histogram vectors the kernel collects the number of times a color occurs in the graph in every iteration.
Linear dynamical systems can be solved exactly, in contrast to most nonlinear ones. Occasionally, a nonlinear system can be solved exactly by a change of variables to a linear system. Moreover, the solutions of (almost) any nonlinear system can be well-approximated by an equivalent linear system near its fixed points. Hence, understanding ...
This solution forms the basis of the convolution method of numerical smoothing and differentiation. Suppose that the data consists of a set of n points ( x j , y j ) ( j = 1, ..., n ), where x j is an independent variable and y j is a datum value.