Multichannel Time Series Analysis with Digital Computer Programs
Multichannel Time Series Analysis with Digital Computer Programs
FORTRAN Codes for Mathematical Programming: Linear, Quadratic and Discrete
FORTRAN Codes for Mathematical Programming: Linear, Quadratic and Discrete
EURASIP Journal on Applied Signal Processing
IEEE Transactions on Signal Processing
Blind equalization of time errors in a time-interleaved ADC system
IEEE Transactions on Signal Processing
Design of hybrid filter banks for analog/digital conversion
IEEE Transactions on Signal Processing
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Published methods that employ a filter bank for compensating the timing and bandwidth mismatches of an M-channel time-interleaved analog-to-digital converter (TIADC) were developed based on the fact that each sub-ADC channel is a downsampled version of the analog input. The output of each sub-ADC is filtered in such a way that, when all the filter outputs are summed, the aliasing components are minimized. If each channel of the filter bank has N coefficients, the optimization of the coefficients requires computing the inverse of an MN × MN matrix if the weighted least squares (WLS) technique is used as the optimization tool. In this paper, we present a multichannel filtering approach for TIADC mismatch compensation. We apply the generalized sampling theorem to directly estimate the ideal output of each sub-ADC using the outputs of all the sub-ADCs. If the WLS technique is used as the optimization tool, the dimension of the matrix to be inversed is N × N. For the same number of coefficients (and also the same spurious component performance given sufficient arithmetic precision), our technique is computationally less complex and more robust than the filter-bank approach. If mixed integer linear programming is used as the optimization tool to produce filters with coefficient values that are integer powers of two, our technique produces a saving in computing resources by a factor of approximately (100.2N(M-1))/(M-1) in the TIADC filter design.