zeros can be used to avoid the dreaded NaN in model failure

### Syntax

```
X = zeros(n,m,'like',sdpvar)
```

### Examples

The typical scenario when we would use zeros is when we want to create a matrix which is almost all zeros, except for some elements.

The following version will fail as discussed in the post NaN in model

```
y = sdpvar(1,1);
X = zeros(5,5);
X(1,5) = y;
```

A natural way around this issue is to simply construct the matrix using concatenation

```
y = sdpvar(1,1);
X = [zeros(1,4) y;zeros(4,5)];
```

An alternative is to first create an overloaded zero, which is nothing but an sdpvar without any variables

```
y = sdpvar(1,1);
X = zeros(5,5,'like',sdpvar);
X(1,5) = y;
```

This only works in recent MATLAB versions though. An ugly alternative is double2sdpvar

```
y = sdpvar(1,1);
X = double2sdpvar(zeros(5,5))
X(1,5) = y;
```