Computed Tomography Technologist Practice Exam 2025 – All-in-One Guide for Exam Success!

The correct answer is the Nyquist Theorem, which is closely associated with the Sampling Theorem in signal processing and information theory. The theorem establishes the principle that a continuous signal can be completely represented in its samples and fully reconstructed from those samples if it is sampled at a rate that is at least twice the highest frequency present in the signal. This minimum sampling rate is referred to as the Nyquist rate.

Understanding the Nyquist Theorem is fundamental in digital signal processing, as it helps ensure that signals are sampled adequately to avoid aliasing, which is the distortion that occurs when different signals become indistinguishable when sampled. This principle has wide-ranging applications in audio processing, telecommunications, and image processing, ensuring that digital representations maintain high fidelity to their analog counterparts.

The other options refer to different concepts associated with signal processing or imaging. The Fourier Theorem pertains to the transformation of functions into oscillatory forms, while the Sharpening Theorem relates to image enhancement techniques. The Resolution Theorem typically involves discussions of spatial resolution in imaging systems but does not directly relate to the sampling process as defined by the Nyquist framework.