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Analog Vs Digital Filter | Difference between Analog and Digital Filter

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The primary difference between the analog and the digital filter is that a digital filter needs to sample the input signal (analog signal) and then convert it into binary numbers. These numbers are stacked (stored) as digital data in a system hard drive, treated, and manipulated digitally. On the other hand, an analog filter does not need to go through such conversion, instead, the signal stays in its analog form throughout the process of filtering.

Digital Filters

A digital filter needs an Analog to Digital Converter (ADC) in order to convert an analog signal into a set of binary numbers. A very fast and robust microprocessor unit processes these binary numbers. After processing, they are sent to another circuit known as Digital-to-Analog Converter (DAC) in order to convert the binary numbers back into an analog signal.

Analog Filters

Analog filters, as mentioned earlier, do not need to convert the signal into a digital one which means they do not require any ADC or DAC converters. In such filters, signal stays in its genuine analog form throughout the processing. Resistor-Capacitor (RC) electronic networks perform the filtering.

This article explains the main differences between analog and digital filter base on factors such as representation, components, frequency response, stability, flexibility, adaptability, environmental changes, additive noise, cost, design, and applications.

Difference between Analog and Digital Filter

Characteristics Analog Filter Digital Filter
Working signalsThese filters work with analog or actual signalsThese filters work with digital samples of the signal
RepresentationThese filters are represented by linear differential equationsThese filters are represented by linear difference equations
ComponentsImplementing such filters requires resistors, inductors, and capacitorsImplementing such filters requires adders, subtractors, and delays
Frequency responseApproximation problem is computed in order to achieve the desired frequency responseSpecial coefficients are designed in order to meet the expected frequency response
Stable & Causal ResponseTransfer function G(s) should be a rational function of laplace variable s, whose coefficients are real numbers.Transfer function G(s) should be a rational function of z-transform z, whose coefficients are real numbers.
Stability & Causality in terms of PolesPoles of transfer function should lie on left-half of s-planePoles of transfer function should lie inside the unit circle of z-plane
Environmental changesBecause of components tolerance, these filters are more sensitive to environmental changesThese types of filters are less sensitive towards environmental changes, noise, and disturbances.
FlexibilityThey are less flexible in natureThey are more flexible because software and control programs can be modified easily according to the requirements.
AdaptabilityThese types of filter are less adaptive; we have to redesign the filter if we want to make any changes.These types of filter are more adaptive because they are programmable; which means that we can make any changes in it without affecting the filter circuitry.
Additive noiseThese filters introduce thermal noise due to componentsThese filters introduce digital noise because of quantization process
CostHigher because of analog components involvementLess costly
CoefficientsNot programmableProgrammable; that’s why easy to make changes
DesignDifficult to design and then simulate because of several componentsSignificantly easy to design and simulate on software program
ADC, DAC, AND DSP RequirementIn such filters, there is no need for ADC, DAC, and DSPThese filters need high performance ADC, DAC, and DSP tools

Advantages of Analog Filters

  • It is quite easy to apply, as there is no need for a microprocessor.
  • There is no need to write a program/algorithm.
  • Easy RC filters need very few components.

Advantages of Digital Filters

  • In advanced appliances that already use a microprocessor, a digital filter will demand very few extra components.
  • Since digital filters are simply software modules, they can be easily standardized.
  • Digital filters are capable of filtering very low frequencies.
  • They are adaptive in nature; which means that their characteristics can be changed based on input signal parameters.
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About Ahmad Faizan

Mr. Ahmed Faizan Sheikh, M.Sc. (USA), Research Fellow (USA), a member of IEEE & CIGRE, is a Fulbright Alumnus and earned his Master’s Degree in Electrical and Power Engineering from Kansas State University, USA.