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By Simon Haykin

This collaborative paintings provides the result of over two decades of pioneering examine through Professor Simon Haykin and his colleagues, facing using adaptive radar sign processing to account for the nonstationary nature of our surroundings. those effects have profound implications for defense-related sign processing and distant sensing. References are supplied in each one bankruptcy guiding the reader to the unique study on which this publication is predicated.

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22) k =0 The Adaptive Spectrum While the lower-order eigenspectra have excellent bias properties, there is some degradation as k increases toward 2NW. In his 1982 paper [36], Thomson introduces a set of weights {dk ( f )} that downweight the higher order eigenspectra. He derives 8 The name multiple-window or multi-taper is the result of using a multiplicity of windows in the spectrum estimation process instead of just one, as is commonly the practice. This reduces the variance while increasing somewhat the bias in the estimation procedure.

Also, since the signal power concentration within the analysis band is large (eigenvalues close to one), the bias introduced from the multiplicity of windows is kept small. 5 TEST DATASET AND A COMPARISON OF SOME POPULAR SPECTRUM ESTIMATION PROCEDURES In order to check our understanding of the multi-taper method, at each stage of the development, we try to implement it on a known test dataset. This set consists of a complex time series of N = 64 points as described in reference 22. 4 Low-pass/high-pass frequency response.

The first pair is consistent with our model and has a larger F value, so it is the one we pick. The advantage with this particular representation is that we can project the maximum of F(f, Δ f) onto the f-axis and resolve the doublet from a simpler, onedimensional function. Note, however, the appearance of spurious peaks, particularly near the edges of the window boundary. These are explained by the fact that the sliding window (Fig. 4) is not an ideal bandpass filter; hence, energy from outside the window, particularly near the window boundaries, can affect the estimation inside the window.

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