the conversion of photon energy into heat that increases electrical resistance

The change in resistance in a semiconductor when exposed to light

The release of photons in response to applied voltage

the emission of charge carriers from a material when it absorbs photons

Measuring heat transfer through conduction in solid materials

Measuring short distances with high precision

Detecting natural thermal emissions from objects at room temperature

Sensing blackbody radiation in the ultraviolet range

Apply a window function, such as a Hanning or Hamming window, before the FFT

Increase the amplitude of the input signal

Use a higher ADC resolution

Use a bandpass filter before sampling to isolate the signal's frequency

The ADC introduces harmonic distortion due to non-linearity in its transfer curve

The signal frequency does not align exactly with one of the FFT’s discrete frequency bins

The signal was sampled below its Nyquist frequency

The sampling rate was unnecessarily high, stretching the FFT's resolution

Aliasing

Quantisation noise

Mains noise

Spectral leakage

The FFT is a less accurate version of the DFT

The FFT is an efficient algorithm for computing the DFT

The FFT is used for analog signals, while the DFT is for digital signals

The FFT is the inverse operation of the DFT

A high-pass filter to remove low-frequency trends

An averaging filter, such as a moving average

An adaptive filter to adjust to changing noise characteristics

A wavelet transform for localised feature preservation

It avoids the use of filtering by directly analysing the raw signal.

It eliminates the need for analog signal conditioning

It allows systems to adjust in real-time to changes in signal properties or the surrounding environment

It ensures the signal environment remains stationary during operation.