Write a function called `GenMat` that takes a 2D array of numbers `inMat` and produces an array called `outMat2`. The function copies the input array `inMat` to the output variable `outMat2` except:

1. Replace the first and last elements of the first row with the mean and standard deviation of the first row, respectively.
2. Replace the first and last elements of the last row with the mean and standard deviation of the last row, respectively.

For example, for the given 4x4 `inMat`:

```
inMat = [ 10 10 30 40;
59 19 70 30;
12 13 32 15;
38 44 55 47];
```

On calling `GenMat`:

```
[outMat1, outMat2] = GenMat(inMat)
```

produces:

```
outMat2 =
22.5000 10.0000 30.0000 15.0000
59.0000 19.0000 70.0000 30.0000
12.0000 13.0000 32.0000 15.0000
46.0000 44.0000 55.0000 7.0711
```

Sure, here's a function called GenMat that takes a 2D array of numbers inMat and produces an array called outMat2 with the required modifications:

function [outMat1, outMat2] = GenMat(inMat)

% calculate the mean and standard deviation of the first row
meanFirst = mean(inMat(1,:));
stdFirst = std(inMat(1,:));

% calculate the mean and standard deviation of the last row
meanLast = mean(inMat(end,:));
stdLast = std(inMat(end,:));

% create a copy of the input array
outMat1 = inMat;

% modify the first row
outMat1(1,1) = meanFirst;
outMat1(1,end) = stdFirst;

% modify the last row
outMat1(end,1) = meanLast;
outMat1(end,end) = stdLast;

% create a copy of the modified input array
outMat2 = outMat1;

end

To use this function with the given example input, you can call it like this:

inMat = [10 10 30 40; 59 19 70 30; 12 13 32 15; 38 44 55 47];
[outMat1, outMat2] = GenMat(inMat);

This will produce the expected output:

outMat2 =

22.5000 10.0000 30.0000 15.0000
59.0000 19.0000 70.0000 30.0000
12.0000 13.0000 32.0000 15.0000
46.0000 44.0000 55.0000 7.0711

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