Titlebook: Smartphone-Based Real-Time Digital Signal Processing; Nasser Kehtarnavaz,Shane Parris,Abhishek Sehgal Book 2015 Springer Nature Switzerlan

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Nasser Kehtarnavaz,Shane Parris,Abhishek Sehgal algorithms could classify the techniques used with .86% accuracy. The accuracy of technique classification was improved even further by applying hierarchical classification, classifying techniques separately for each limb. Only 10% of the dataset was required as training set to approach the observe

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different point values to the offensive and defensive units of the same play, which is the rational thing to do especially in a league with an uneven schedule such as the NFL. The average absolute difference between the raw and adjusted points is 0.07 points/play (p-value < 0.001), while the median

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Book 2015 now become powerful processing platforms has led to the development of this book, thus enabling students to use their own smartphones to run signal processing algorithms in real-time considering that these days nearly all students possess smartphones. Changing the hardware platforms that are curren

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1932-1236 g courses in many engineering programs for the purpose of teaching students the technical know-how for putting signal processing algorithms or theory into practical use. These courses normally involve access to a teaching laboratory that is equipped with hardware boards, in particular DSP boards, to

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Fixed-Point vs. Floating-Point, the CPU possesses the necessary hardware for manipulating both of these parts. As a result, in general, floating-point operations involve more logic elements (larger ALU) and more cycles (more time) to manipulate floating-point values.

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Introduction,epts by covering practical aspects of implementing signal processing algorithms. DSP processor boards are often deployed in these courses. To a lesser extent, ARM-based boards such as Raspberry Pi [1] are utilized. A number of textbooks are available discussing how to implement signal processing alg

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Analog-to-Digital Signal Conversion,es. Sampling and quantization constitute the steps needed to achieve analog-to-digital signal conversion. To minimize any loss of information that may occur as a result of this conversion, it is important to understand the underlying principles behind sampling and quantization.