1. A simplified constellation pattern recognition and parallel processing classification apparatus for a software-defined communications device, comprising: an r(k) noisy input data having an unknown constellation pattern, where k=1, 2,. .. , K; a digital signal processor estimates a function σ 2 , where σ is a standard deviation (std) of the white Gaussian noise n(k); said digital signal processor having a stored look-up table, a means for selecting test functions, and a means for classifying a pattern; a means for calculating computes a function CN i using a plurality of add and multiply components, where N i is a positive number and where C = 2 ⁢ σ 2 ⁢ K log 2 ⁢ ⅇ = 1.3863 ⁢ ⁢ σ 2 ⁢ K ; said calculating means computes a function r T ·{circumflex over (β)} (i) using a dot product component, where T is a threshold chosen by the user and where β (i) (k) is an unknown discrete random variable that is uniformly distributed over the alphabet set {b 1 (i) , b 2 (i) ,. .. , b M i (i) } with a zero mean value; a means for estimating estimates a function {circumflex over (β)} (i) using said lookup table; said calculating means computes a function {circumflex over (β)} (i) T ·{circumflex over (β)} (i) using said dot product component; said calculating means and said estimating means compare said functions; said calculating means to determines a plurality of parallel likelihood test functions for an i th hypothesis H i , where i=1, 2,. .. , L; said test function selection means selects an optimal likelihood test function from said plurality of parallel test functions; and said pattern classification means uses said optimal likelihood test function and said i th hypothesis H i to rapidly detect said unknown constellation pattern with a reduced level of computational complexity to determine a modulation scheme for said unknown constellation pattern.