Abstract
The kernel recursive least squares (KRLS) algorithm performs non-linear regression in an online manner, with similar computational requirements to linear techniques. In this paper, an implementation of the KRLS algorithm utilising pipelining and vectorisation for performance; and microcoding for reusability is described. The design can be scaled to allow tradeoffs between capacity, performance and area. Compared with a central processing unit (CPU) and digital signal processor (DSP), the processor improves on execution time, latency and energy consumption by factors of 5, 5 and 12 respectively.
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