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 signals | These filters work with analog or actual signals | These filters work with digital samples of the signal |
| Representation | These filters are represented by linear differential equations | These filters are represented by linear difference equations |
| Components | Implementing such filters requires resistors, inductors, and capacitors | Implementing such filters requires adders, subtractors, and delays |
| Frequency response | Approximation problem is computed in order to achieve the desired frequency response | Special coefficients are designed in order to meet the expected frequency response |
| Stable & Causal Response | Transfer 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 Poles | Poles of transfer function should lie on left-half of s-plane | Poles of transfer function should lie inside the unit circle of z-plane |
| Environmental changes | Because of components tolerance, these filters are more sensitive to environmental changes | These types of filters are less sensitive towards environmental changes, noise, and disturbances. |
| Flexibility | They are less flexible in nature | They are more flexible because software and control programs can be modified easily according to the requirements. |
| Adaptability | These 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 noise | These filters introduce thermal noise due to components | These filters introduce digital noise because of quantization process |
| Cost | Higher because of analog components involvement | Less costly |
| Coefficients | Not programmable | Programmable; that’s why easy to make changes |
| Design | Difficult to design and then simulate because of several components | Significantly easy to design and simulate on software program |
| ADC, DAC, AND DSP Requirement | In such filters, there is no need for ADC, DAC, and DSP | These 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.
