The noise reference input contains noise related to that of the main input (like background noise). The second input is a noise reference input. One input contains the speech signal corrupted by the noise. The adaptive filtering system uses two inputs. An adaptive filtering system uses a noise cancellation model to eliminate as much of this noise as possible. An example might be an automotive application. Assume a speech signal is buried in a very noisy environment with many periodic frequency components lying in the same bandwidth as the speech signal. Adaptive filtering is used in cases where a speech signal must be extracted from a noisy environment. Adaptive FIR FilterĪ common form of a FIR filter is called an adaptive filter. If we use a 21 tap linear-phase FIR filter operating at a 1 kHz rate, the delay is computed as: Linear-phase filters delay the input signal, but don't distort its phase. If the coefficients are symmetrical in nature, the filter is called a linear-phase filter. This is referred to as the phase delay of the filter. How long it takes for the output to go to zero is dependent on the filter length, which is defined by the number of taps (a multiplication of a delayed sample) as well as the sample rate (how quickly the taps are being computed) The time it takes for the FIR filter to compute all of the filter taps defines the delay from when a sample is input to the system and when a resultant sample is output. A more general way of stating this phenomenon is that, regardless of the type of signal input to the filter or how the long we apply the signal to the filter, the output will eventually go to zero. If you put in an impulse as described earlier, zeroes will eventually be output after the “1” valued sample has made its way in the delay line past all the filter coefficients. We call the impulse response “finite” because there is no feedback loop in this form of filter. In other words if you put an “impulse” into a FIR filter which consists of a “1” sample followed by a large number of “0” samples, the output of the filter will be simply the set of coefficients, as the 1 valued sample moves past each coefficient in turn to form the output. The “impulse response” of a FIR filter is just the set of FIR coefficients. Robert Oshana, in DSP Software Development Techniques for Embedded and Real-Time Systems, 2006 FIR Filter Characteristics
0 Comments
Leave a Reply. |
Details
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |