name a linear filter and a non-linear filter,describe the details of procedures

A linear filter is a filter whose output only depends on a linear combination of its input. One example of a linear filter is the moving average filter. The moving average filter works by taking the average of the input signal over a certain window of time. The output of the filter is the sum of the values in the window divided by the window size.

The procedure for implementing a moving average filter is as follows:

1. Determine the window size. This is the number of samples that will be averaged together in each step of the filter.

2. Initialize the output signal to be an empty array.

3. Loop through the input signal, starting from the beginning.

4. For each sample in the input signal, compute the average of the samples in the window centered around that sample.

5. Append the computed average to the output signal.

6. Continue until all samples in the input signal have been processed.

A non-linear filter, on the other hand, is a filter whose output depends on a non-linear function of its input. An example of a non-linear filter is the median filter. The median filter works by replacing each sample in the input signal with the median of a window of surrounding samples.

The procedure for implementing a median filter is as follows:

1. Determine the window size. This is the number of samples that will be used to compute the median in each step of the filter.

2. Initialize the output signal to be an empty array.

3. Loop through the input signal, starting from the beginning.

4. For each sample in the input signal, collect the samples in the window centered around that sample.

5. Compute the median of the collected samples.

6. Replace the current sample with the computed median.

7. Append the replaced sample to the output signal.

8. Continue until all samples in the input signal have been processed.