![]() See Figure 2 for a visual representation of the difference between the two. Filtering is optimized based on the processing end goal, while spectral analysis is concerned with the frequency makeup. Gleaning useful information from signals often requires the use of filtering and/or spectral analysis functions. See Figure 1 from for some examples.įigure 1 Examples of applications for Digital Signal Processing (DSP) These applications are both numerous and highly varied. Next it is digitized, at which point it can be processed further depending on the application. First a transducer converts the analog input into an electrical signal. To achieve this, an analog signal needs to go through a few more steps of processing. This process, which occurs so effortlessly via our analog signal processing brain, has been the focus of decades of research and development in order to replicate and exceed a human’s capabilities on digital computers. A sensation is converted into electrical signals that are transmitted via our nervous system for the brain to interpret and respond accordingly. The human brain is an excellent processor for our world of analog data, which comes to us through our sensory organs. Signals come in a variety of formats, from sound to vibrations to moving images. Limited to critical applications initially, the increased access/affordability of computers necessitated the broad and frequent use of this algorithm. In the 1960’s the Fast Fourier Transform (FFT) was developed, enabling efficient solutions of the discrete FT for practical problems. Though applications for this transform were few during its inception in the 19 th century, it became the foundation upon which modern signal processing was built. This game-changing mathematical method long predates a smartphone however. The modern world is bursting with signals that are virtually meaningless until they can be processed or transformed. Doing the same with the engineers at Rock West will immediately pique their interest and likely prompt a discussion about how the Fourier transform (FT) is at the heart of signal processing today. If you were to mention Joseph Fourier to an average passerby in a crowd, you would likely get very little reaction. To fully utilize the power of this digital transformation, it is important to understand how it works. And yet, the potential of this process is continually underestimated. So vast is the power of signal processing to completely change an industry, or change the way we live our lives, it is not quantifiable. military to audio sound engineers to the healthcare industry deal in the signal processing arena each and every day. Signal processing is a science that has unlimited applications. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |