In this letter we propose simple and robust features to distinguish continuous-phase frequency shift keying from quadrature amplitude modulation and phase shift keying modulations. The features are based on sample mean and sample variance of the imaginary part of the product of two consecutive complex signal values. Root raised cosine pulses are used to generate the linearly modulated signals. Support vector machines are employed to distinguish the signals. One benefit of using support vector machines is that it requires very few realizations for training. Moreover, no a priori information is required about carrier amplitude, carrier phase, carrier offset, symbol rate, pulse shape, initial symbol phase (timing offset) and channel impulse response. Effectiveness of the features and signal separation by support vector machines is tested by observing the joint effects of additive white Gaussian noise, carrier offset, lack of symbol and sampling synchronization, and either fast or slow fading. In the course of doing that, the proposed classifier is compared to the wavelet based classifier, equipped by support vector machines.