Data compression techniques are classified into four categories which describe the effect a compression method has on the form of the signal transmitted. Each category is defined and examples of techniques in each category are given. Compression methods which have received previous investigation, such as the geometric aperture methods, as well as techniques which have not received much attention, such as Fourier filter, optimum discrete filter, and variable sampling rate compression, are described. Results of computer simulations with real data are presented for each method in terms of rms and peak errors versus compression ratio. It is shown that, in general, the geometric aperture techniques give results comparable to or better than the more "exotic" methods and are more economical to implement at the present state-of-the-art. In addition, the aperture compression methods provide bounded peak error which is not readily obtainable with other methods. A general system design is given for a stored-logic data compression system with adaptive buffer control to prevent loss of data and to provide efficient transmission of multiplexed channels with compressed data. An adaptive buffer design is described which is shown to be practical, based on computer simulations with five different types of representative data.