Abstract: Sets of coefficient polynomials are used to design embedded-component architectures that have capability for asynchronous parallel execution at an advantageous arithmetic level where algebraic merging is realized with other operations, algorithms or applications. Asynchronous parallel execution is use to produce image cross-correlation from a freshly-created target image and a pre-existing filter image. Arrays of pixels for both images are input to Cauchy registers where a correlation value is computed by obtaining the sum of all the individual products of corresponding pixels from the target image and the filter image. The cross-correlation value is obtained by the accumulation of each corresponding bit of the individual bit positions of each Cauchy product into a set of coefficient polynomials of the final cross-correlation value. The final cross-correlation value is input to a suitable tracking means to increase the level of accuracy and case in recognizing and tracking a potential target.

Abstract: Sets of coefficient polynomials are used to design embedded-component architectures that have capability for asynchronous parallel execution at an advantageous arithmetic level where algebraic merging is realized with other operations, algorithms or applications. Because of the particular hardware structures made possible by the use of CPA, higher computational granularities and complex modules are more easily feasible than by using conventional arithmetic and, additionally, increased efficiency is obtained for algorithmic computations involving single and multiple operations. This is achieved by the merging of operations and the integration of algorithms, and thereby avoiding the necessity of performing the entire basic arithmetic separately for each operation or algorithm.

Abstract: Sets of coefficient polynomials are used to design embedded-component architectures that have capability for asynchronous parallel execution at an advantageous arithmetic level where algebraic merging is realized with other operations, algorithms or applications. Because of the particular hardware structures made possible by the use of CPA, higher computational granularities and complex modules are more easily feasible than by using conventional arithmetic and, additionally, increased efficiency is obtained for algorithmic computations involving single and multiple operations. This is achieved by the merging of operations and the integration of algorithms, and thereby avoiding the necessity of performing the entire basic arithmetic separately for each operation or algorithm.