# Time Series Analysis vs. DSP Terminology

### Digital signal processing and time series analysis are very similar — but the terminology that they use is very different. This article is here to clarify the confusion.

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Join For FreeTime series analysis and digital signal processing are closely related. Unfortunately, the two fields use different terms to refer to the same things.

Suppose you have a sequence of inputs *x*[*n*] and a sequence of outputs *y*[*n*] for integers *n*.

## Moving Average/FIR

If each output depends on a linear combination of a finite number of previous *inputs*:

...then time series analysis would call this a **moving average** (MA) model of order *q*, provided *b*_{0} = 1. Note that this might not really be an average, i.e. the *b*s are not necessarily positive and don't necessarily sum to 1.

Digital signal processing would call this a **finite impulse response** (FIR) filter of order *q*.

## Autoregressive/IIR

If each output depends on a linear combination of a finite number of previous *outputs*:

...then time series analysis would call this an **autoregressive** (AR) model of order *p*.

Digital signal processing would call this an **infinite impulse response** (IIR) filter of order *p. *

Sometimes, you'll see the opposite sign convention on the *a*s.

## ARMA/IIR

If each output depends on a linear combination of a finite number of previous inputs *and* outputs:

...then time series analysis would call this an **autoregressive moving average **(ARMA) model of order *(p*, *q*), i.e. *p* AR terms and *q* MA terms.

Digital signal processing would call this an **infinite impulse response** (IIR) filter with *q* feedforward coefficients and *p* feedback coefficients. Also, as above, you may see the opposite sign convention on the *a*s.

## ARMA Notation

Box and Jenkins use *a*s for input and *z*s for output. We'll stick with *x*s and *y*s to make the comparison to DSP easier.

Using the backward shift operator *B* that takes a sample at *n* to the sample at *n*-1, the ARMA system can be written as:

...where φ and θ are polynomials, and:

## System Function Notation

In DSP, filters are described by their **system function**, the *z*-transform of the impulse response. In this notation (as in Oppenheim and Shafer, for example), we have:

## Related

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