By Phil Lapsley, Jeff Bier, Amit Shoham, Edward A. Lee
This state-of-the-art, functional advisor brings you an self sufficient, finished advent to DSP processor know-how. a radical educational and evaluate of DSP architectures, this e-book encompasses a vast variety of todays product choices in examples that illustrate DSP positive factors and functions. This ebook is mainly priceless to digital platforms designers, processor architects, engineering managers, and product planners.From the again CoverElectrical Engineering/Signal Processing DSP Processor basics Architectures and contours A quantity within the IEEE Press sequence on sign Processing Jerry D. Gilbson, sequence Editor because the emergence of the 1st commercially profitable electronic sign processors within the early Eighties, the programmable DSP industry has burgeoned. Designers can now make a choice from an unlimited array of specialised processors with strong signal-processing services. DSP Processor basics provides an autonomous, finished advent to DSP processor know-how. a radical instructional and evaluate of DSP architectures, this ebook contains a extensive diversity of today’s product choices in examples that illustrate DSP positive aspects and services. This booklet is principally worthwhile to digital platforms designers, processor architects, engineering managers, and product planners. subject matters coated include:•Numeric formats•Data paths•Memory structures•Instruction sets•Execution control•Pipelining•On-chip peripherals•On-chip debugging facilities•Clocking options•And more!sharingmatrix.com
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Extra info for DSP Processor Fundamentals: Architectures and Features
Similarly, since the magnitude of the largest representable value is reduced, but the magnitude of the smallest representable value is unchanged, so dynamic range is reduced. Thus, scaling must be done with great care, balancing the need to reduce or eliminate the possibility of overflow with the need to maintain adequate dynamic range and precision. Proper scaling of signals can be a significant challenge in implementing an application on a fixed-point processor. Typically, application developers use detailed simulations and analysis to determine where and by how much signals should be scaled and then insert scaling operations at the appropriate locations.
Scaling is used to maintain precision by modifying the range of signal values to be near the maximum range of the numeric representation used. " Using this same definition for a floating-point format, the maximum available precision is the number of bits in the mantissa, including the implied integer bit. " Example 1: = 2 6 + 24 + 2 1 + 2° = 64 + 16 + 2 + 1 = 83 Example 2: = =_2 7 + 25 + 23 + 2 2 =-128 + 32 + 8 + 4 = -84 FIGURE 3-2. Simple binary Integer representation. This form is called two's complement representation.
For high-volume products, custom hardware may also be less expensive than a DSP processor. This is because a custom implementation places in hardware only those functions needed by the application, whereas a nsp processor requires every application to pay for the full functionality of the processor, even if it uses only a small subset of its capabilities. Of course, developing custom hardware has some serious drawbacks in addition to these advantages. Most notable among these drawbacks are the effort and expense associated with custom hardware development, especially for custom chip design.