### Create and Apply Standard Kalman Filter in Go

Source: https://github.com/konimarti/kalman/blob/master/README.md

Demonstrates how to initialize a Kalman filter with discrete state-space matrices and noise covariances, set up the initial context, and apply the filter to new measurements and control inputs.

```Go
import (
	"github.com/konimarti/kalman"
	"github.com/konimarti/kalman/lti"
)

// ... inside a function ...

// create filter
filter := kalman.NewFilter(
	lti.Discrete{
		Ad, // prediction matrix (n x n)
		Bd, // control matrix (n x k)
		C,  // measurement matrix (l x n)
		D,  // measurement matrix (l x k)
	},
	kalman.Noise{
		Q, // process model covariance matrix (n x n)
		R, // measurement errors (l x l)
	},
)

// create context
ctx := kalman.Context{
	X, // initial state (n x 1)
	P, // initial process covariance (n x n)
}

// get measurement (l x 1) and control (k x 1) vectors
// ..

// apply filter
filteredMeasurement := filter.Apply(&ctx, measurement, control)
}
```

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