Broadband Smoothing
- Reduces noise and improves the signal-to-noise ratio in broadband signals through averaging or filtering.
- Applied across telecommunications, engineering, and medical imaging to clarify signals or improve measurement accuracy.
- Common implementations include moving average, low-pass, and high-pass filters.
Definition
Section titled “Definition”Broadband smoothing, also known as signal averaging or filtering, is a technique used to reduce noise and improve the signal-to-noise ratio in a broadband signal.
Explanation
Section titled “Explanation”Broadband smoothing cleans up noisy or distorted broadband signals by reducing noise components. In telecommunications it improves transmitted signal quality affected by interference, noise, and distortion. In engineering it improves the accuracy of signal measurements by reducing noise that would otherwise bias readings. In medical imaging it reduces image noise (for example in CT scans) so details become easier to see. Common methods for broadband smoothing include moving average filters, low-pass filters, and high-pass filters.
Examples
Section titled “Examples”Telecommunications
Section titled “Telecommunications”When a signal is transmitted over a long distance, it can be affected by interference, noise, and distortion. These factors can make the signal noisy and distorted, reducing communication quality. Broadband smoothing can clean up the signal to make it clearer and more intelligible.
Engineering
Section titled “Engineering”When measuring signal strength, noise or other factors can make measurements inaccurate. Broadband smoothing reduces noise and other disturbances, improving measurement accuracy.
Medical imaging
Section titled “Medical imaging”In CT scans, image noise can obscure body details. Broadband smoothing reduces noise and improves image quality, making details easier to see.
Methods
Section titled “Methods”Moving average filters
Section titled “Moving average filters”A moving average filter takes the average of multiple samples of the signal to reduce noise and improve the signal-to-noise ratio. Example: if a signal is measured 10 times with values 5, 10, 8, 9, 6, 7, 11, 9, 5, and 8, the moving average filter would take the average of these measurements, which is 7.8. This value would then be used as the filtered signal.
Low-pass filters
Section titled “Low-pass filters”A low-pass filter allows low-frequency signals to pass while blocking high-frequency signals, removing high-frequency noise. Example: given measurements 5, 10, 8, 9, 6, 7, 11, 9, 5, and 8, the low-pass filter would remove the high-frequency signals, such as the 11 and the 5, and only allow the low-frequency signals, such as the 8 and the 9, to pass through.
High-pass filters
Section titled “High-pass filters”A high-pass filter allows high-frequency signals to pass while blocking low-frequency signals, removing low-frequency noise. Example: given measurements 5, 10, 8, 9, 6, 7, 11, 9, 5, and 8, the high-pass filter would remove the low-frequency signals, such as the 5 and the 6, and only allow the high-frequency signals, such as the 11 and the 10, to pass through.
Use cases
Section titled “Use cases”- Telecommunications: improve transmitted signal quality over long distances.
- Engineering: improve accuracy of measurements by reducing noise.
- Medical imaging: improve image quality (for example, CT scans) by reducing noise.
Related terms
Section titled “Related terms”- Signal averaging
- Filtering
- Moving average filter
- Low-pass filter
- High-pass filter
- Signal-to-noise ratio