By E.S. Gopi

### Kurzbeschreibung

The Algorithms resembling SVD, Eigen decomposition, Gaussian combination version, HMM and so on. are shortly scattered in several fields. There continues to be a necessity to assemble all such algorithms for speedy reference. additionally there's the necessity to view such algorithms in program perspective. This e-book makes an attempt to meet the above requirement. The algorithms are made transparent utilizing MATLAB courses.

### Buchrückseite

The Algorithms similar to SVD, Eigen decomposition, Gaussian mix version, HMM and so forth. are scattered in several fields. there's the necessity to acquire all such algorithms for fast reference. additionally there's the necessity to view such algorithms in software viewpoint. set of rules Collections for electronic sign Processing purposes utilizing MATLAB makes an attempt to fulfill the above requirement. additionally the algorithms are made transparent utilizing MATLAB courses.

**Read Online or Download Algorithm Collections for Digital Signal Processing Applications using Matlab PDF**

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**Additional info for Algorithm Collections for Digital Signal Processing Applications using Matlab **

**Example text**

1. The matrices A and B are given below. A= 9 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 9 1. Artificial Intelligence B= 9 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 49 0 0 0 9 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 9 Initial orders selected by the four ants are displayed below. ANT1: ANT2: ANT3: ANT4: 5 3 5 6 4 7 1 1 2 8 7 7 1 5 2 2 3 2 4 8 6 1 3 5 7 4 6 3 8 6 8 4 Number of ants used to find the optimum order is 4.

3 (say) as shown in the Figure 1-17 and Figure 1-18 given below. Figure 1-17. Xinput as the crisp input for the variable X 36 Chapter 1 Figure 1-18. 2 as shown in the figure given below Step 2: Fuzzy input to fuzzy output mapping using fuzzy base rule Fuzzy base rule is the set of rules relating the fuzzy input and fuzzy output of the fuzzy based system. Let us consider the Fuzzy Base Rule as shown in the table given below. Table 1-1. 2) Fuzzy output set is obtained in two stages. 1. 3)} Ylarge Zsmall Zlarge Zmedium 1.

Table 1-4. Updating Pheromone Matrix 1 2 3 4 5 6 7 1 1/C4 1/C1 0 0 1/C3 0 0 1/C2+1/C5 2 1/C2 1/C3 0 0 1/C1 1/C5 1/C4 0 3 0 0 1/C1+1/C3 1/C5 1/C2 1/C4 0 0 4 1/C5 1/C2 1/C4 0 0 0 1/C1+1/C3 0 5 0 1/C4 1/C5 1/C3 0 1/C1 1/C2 0 6 0 0 0 1/C1+1/C2 1/C5 1/C3 0 1/C4 7 8 1/C1+1/C3 0 1/C5 0 1/C2 0 1/C4 1/C4 0 1/C2 0 1/C5 0 1/C1+1/C3 0 8 0 1. Artificial Intelligence 47 Step 3: Next set of orders selected by the ants is as described below. • Generate the position sequence randomly 7 8 2 3 6 4 1 5 (say) Let the order decided by the ant1 be represented as [u1 u2 u3 u4 u5 u6 u7 u8 ] • The value for the u7 in the order as mentioned above is selected first as the first number of the randomly generated position sequence is 7.