Stochastic Signal Processing
Ian Young
4.6 ★
store rating
Free
AppRecs review analysis
AppRecs rating 4.4. Trustworthiness 70 out of 100. Review manipulation risk 26 out of 100. Based on a review sample analyzed.
★★★★☆
4.4
AppRecs Rating
Ratings breakdown
5 star
80%
4 star
0%
3 star
20%
2 star
0%
1 star
0%
What to know
✓
Low review manipulation risk
26% review manipulation risk
✓
Credible reviews
70% trustworthiness score from analyzed reviews
✓
High user satisfaction
80% of sampled ratings are 5 stars
About Stochastic Signal Processing
Speech, music, seismic vibrations, oil prices, and climate measurements are all examples of stochastic (random) signals. In this textbook—intended for individuals with prior training in introductory signal processing and introductory probability theory—we develop techniques to process such signals to extract useful information. We present case studies ranging from music to photographic images to oil prices to climate data to the motion of individual biomolecules. This textbook, as an interactive textbook ("iBook"), makes use of your device's ability to display dynamic information through films and animations and to hear the results of the techniques applied to music. At the end of every chapter there are homework problems ranging from easy to "olympic".
A new and exciting aspect is that we make use of your device's interactive capabilities to offer 59 laboratory experiments in signal processing. The experiments use the camera, the microphone, the speakers, and the graphical user interface. These experiments are not simulations; they are examples of real digital processing of signals in your device. In this time of at-home and online learning, this is the way to learn signal processing through study and experimentation.
A new and exciting aspect is that we make use of your device's interactive capabilities to offer 59 laboratory experiments in signal processing. The experiments use the camera, the microphone, the speakers, and the graphical user interface. These experiments are not simulations; they are examples of real digital processing of signals in your device. In this time of at-home and online learning, this is the way to learn signal processing through study and experimentation.