Advancements in digital signal communications have brought a large variety of modulation schemes for transmitting signals. Consequently, reliable detection of the modulation scheme embedded in the received signal has become an important issue in communications. In this research study, a digital signal modulation classifier has been developed using higher order statistical algorithms to detect the modulation scheme in the signals received. The algorithm to identify the modulation schemes is based on the eighth order cumulants extracted from the signals. Noisy channel characteristics of the wireless system was taken into consideration in the design of the algorithm to allow detection of signals with Additive White Gaussian Noise (AWGN) and multipath Rayleigh fading and multipath Ricean fading channels at various levels of Signal to Noise Ratios (SNRs). This paper describes the developed digital signal modulation classification algorithm, and its demonstration on several types of communication signals. The robustness and capabilities of the modulation classification developed are established for reliable detection of the communication signals.