Sensors need to convert physical values such as pressure, weight, distance, and length into a digital value. In the first step of such a conversion, the physical is converted into a temporary electrical analog value such as voltage or time.
Many designers are on a quest to embed intelligence into even the most mundane objects as they try to equip smart homes with intelligent connected devices and sensor networks that link to the burgeoning Internet of Things (IoT). Other embedded designers focus on increasing the capabilities of already-intelligent consumer electronics products or on making portable versions of sophisticated sensing devices that require energy efficiency. Though these intelligent devices often need to run on battery power for a long time – sometimes for a period of years – many also require high performance due to their complexity.
The use of ARM CPUs is growing in Systems-on-Chip (SoC) platforms, as the generic ARM architecture lends well to a wide variety of systems and applications. However, while ARM processors are ideally suited for system management functions, they typically struggle with processing-intensive tasks such as imaging and advanced audio and voice communications. As the need for advanced signal processing continues to increase, application-specific Digital Signal Processors (DSPs) are now being integrated with ARM cores on the die of SoCs to offload demanding data processing from the CPU in order to optimize power consumption and performance.
Fixed-point DSPs store and manipulate integers, while floating-point DSPs use a mantissa and exponent to represent rational numbers. Multiple factors determine whether fixed- or floating-point is the right choice for a particular application, including cost, development time, and performance.
Multicore DSPs allow power-efficient implementation of SAR processing tasks.
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