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Active noise control (ANC) is achieved by introducing a canceling "antinoise" wave through an appropriate array of secondary sources. These secondary sources are interconnected through an electronic system using a specific signal processing algorithm for the particular cancellation scheme. ANC has application to a wide variety of problems in manufacturing, industrial operations, and consumer products. The emphasis of this paper is on the practical aspects of ANC systems in terms of adaptive signal processing and digital signal processing (DSP) implementation for real-world applications. In this paper, the basic adaptive algorithm for ANC is developed and analyzed based on single-channel broad-band feedforward control. This algorithm is then modified for narrow-band feedforward and adaptive feedback control. In turn, these single-channel ANC algorithms are expanded to multiple-channel cases. Various online secondary-path modeling techniques and special adaptive algorithms, such as lattice, frequency-domain, subband, and recursive-least-squares, are also introduced. Applications of these techniques to actual problems are highlighted by several examples.

Teleconferencing systems employ acoustic echo cancelers to reduce echoes that result from coupling between the loudspeaker and microphone. To enhance the sound realism, twochannel audio is necessary. However, in this case (stereophonic sound) the acoustic echo cancellation problem is more difficult to solve because of the necessity to uniquely identify two acoustic paths. In this paper, we explain these problems in detail and give an interesting solution which is much better than previously known solutions. The basic idea is to introduce a small nonlinearity into each channel that has the effect of reducing the interchannel coherence while not being noticeable for speech due to self masking.

Some adaptive signal processing applications, such as wideband active noise control and acoustic echo cancellation, involve adaptive filters with hundreds of taps. The computational burden associated with these long adaptive filters precludes their use for many low-cost applications. In addition, adaptive filters with many taps may also suffer from slow convergence, especially if the reference signal spectrum has a large dynamic range. Subband techniques have been recently developed for adaptive filters to solve these problems. However, the conventional approach is ruled out for many applications because delay is introduced into the signal path. This paper presents a new type of subband adaptive filter architecture in which the adaptive weights are computed in subbands, but collectively transformed into an equivalent set of wideband filter coefficients. In this manner, signal path delay is avoided while retaining the computational and convergence speed advantages of subband processing. An additional benefit accrues through a signifwant reduction of aliasing effects. An example of the general technique is presented for a 32-subband design using a polyphase FF'T implementation. For this example, the number of multiplies required are only about one-third that of a conventional fullband design with zero delay, and only slightly greater than that of a conventional subband design with 16 ms delay.