1. Technical Field
This invention relates to digital filters and particularly to finite impulse response filters.
2. Related Art
Digital signal processing (“DSP”) is used in a wide variety of devices, such as televisions, audio devices, hearing aids, computers and cellular phones. These devices employ DSP techniques to process signals in a variety of ways. For example, digital filtering techniques may be used to improve signal quality or to extract important information. In other cases, digital filters may be used to restore a signal that has been distorted in some way.
A digital filter, such as a finite impulse response (“FIR”) filter, typically includes a number of equally spaced taps. Each tap is separated by a delay line and is multiplied by a filter coefficient. The output of each tap is added together and passed through a reconstruction filter. The filter coefficients allow the impulse response of the filter to be specified.
FIR filters designed to operate at high sample rates often require numerous taps to properly specify waveforms and frequency responses for wide-band signals, such as audio signals. These filters often provide an excessive amount of time or frequency resolution. For example, consider a signal with a bandwidth from 50 Hz to 20 kHz. To avoid aliasing, a sample rate for the signal would typically be selected that is greater than 40 kHz. Wile this high sample rate may be necessary for the high frequency components of the signal, linear sampling across all frequencies results in excessive sampling for the low frequency components. Furthermore, the high sample rate would typically result in a FIR filter with high complexity due to numerous filter coefficients needed to specify the impulse response.
Moreover, the high complexity of FIR filters often creates obstacles to implementation. For example, selection of the suitable filter coefficients to elicit a desired frequency response can be challenging. Filter designers typically employ specialized optimization software to select suitable filter coefficients. If the desired frequency response changes, the filter designer must go through the challenging process of selecting different filter coefficients, likely employing optimization software. These optimization techniques render real-time adjustments to the filter coefficients to meet changing desired frequency responses extremely difficult and costly in terms of processing resources.
Therefore, there exists a need for a FIR filter system particularly suited for filtering non-linearly sampled input signals, with enhanced capability for real-time adjustment of the frequency response.