Hello, a technique that allows something similar to what you are suggesting is to use polyphase filters. The difference is that you will not process contiguous vectors, but (for a 2-phase decomposition example) process the even samples with one stage of the filter and the odd samples with another
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Hi, thanks for the answer so far. A polyphase filter is a nice idea but it does not answer the problem. The signal has to be demultiplexed (decimated), the different streams have to be filtered, the results must be added to get the final output signal. My question has a different target. Imagine
Find the roots, pair the complex conjugate roots and distribute the pairs and single real roots evenly (how exactly?) in the two filters. Matlab at least has facilities finding roots of large polynomials. -olli On Wed, Jan 19, 2011 at 4:56 PM, Uli Brueggemann uli.brueggem...@gmail.com wrote:
Hi Uli I don't know if this will be useful for your situation, but a simple method for decomposing your kernel is to simply chop it in two. So for a kernel: 1 2 3 4 5 6 7 8 You can decompose it into two zero padded kernels: 1 2 3 4 0 0 0 0 0 0 0 0 5 6 7 8 And sum the results of convolving
Thomas, I suppose that a decomposition of a n-taps kernel into n zero-padded kernels would directly lead to the basics of the convolution algorithm :-) But your proposal also introduces a parallel computation, where the results have to be offset and added (incl. overlap treatment). My question is
I see, most people want *more* parallelisation in their algorithms, not less ;) Perhaps you could make a 'guess' at the first filter and then solve the problem of finding a second filter which gives you the desired result. Since: f1*f2=result ...we know f1 f2 and so can find 'result', and...