Passive, active, and digital filters (3ed., CRC, 2009) - tiera.ru

IndexIN-11reflection coefficient,19-42–19-44tap gains, 19-44tapped numerator structure,19-41–19-42third-order one-multiplierinjected numerator filter,19-42–19-43LC ladderzero-producing step, 8-4–8-5zero-shifting step, 8-2–8-4LCM one-port networkadmittance function, 7-3driving-point immittance, 7-2first and second Cauer canonicalform, 7-4first and second Foster canonicalform, 7-3input impedance, 7-1reactance function, 7-2–7-3,7-5–7-6Leapfrog topology, 15-12Learning vector quantization (LVQ)algorithm, 25-25Least squares (L 2 -norm) criterionadaptive weighted least square(WLS), 19-37–19-38eigenfilter approach,19-39–19-40quadratic programming, 19-38transfer function, IIR filter,19-36weighted square error,19-36–19-37LeGall 3,5-tap filter, 24-14–24-15Lifting schemes; see also Ladderstructuresconstructionanalysis polyphase matrixtypes, 24-34–24-35elementary matrix,24-34perfect reconstruction (PR)filter bank, 24-35synthesis polyphase matrix,24-35–24-36implementationdivision process,24-37–24-38dual lifting, 24-38–24-39Matlab function, 24-37scaling matrix, 24-39Linear filtering, 26-7–26-8Linear programming, 22-10–22-11Linear shift-invariant system, 22-2LM-estimationdefinition, 26-11generalized Cauchy density,26-11–26-14arg min and log functions,26-13–26-14error norm, 26-14–26-15GCD function, 26-11–26-12heavy-tailed distribution,26-12impulsive sequence, 26-12minimization problem, 26-13real-valued weights andoptimization,26-26–26-27running meridian smoothers,26-21–26-26medianity parameter,26-21–26-22meridian estimator, 26-22mode–type estimator, d!0,26-23–26-24properties, 26-25sample median, d!1,26-22–26-23sample meridian, 26-21weighted meridian,26-25–26-26running myriad smoothers,26-14–26-21fixed point weighted myriadsearch, 26-21linearity parameter,26-14–26-15minimization problem, 26-18mode–type estimator, g!0,26-17normalized linear estimation,g!1, 26-19no undershoot=overshoot,26-17objective function,26-15–26-16sample mean, g!1,26-16–26-17sample myriad, 26-14shift and sign invariance,26-18unbiasedness, 26-18weighted mode-typeestimation, g!0,26-19–26-20weighted myriad, 26-18Low-gain active filtersfirst-order filter realizations,11-6–11-7first-order transfer functions,11-1–11-2frequency response, 11-4–11-5,11-6, 11-7higher order filters, 11-16–11-17nonideality influencegain-bandwidth,11-23–11-27noise analysis, 11-27–11-29sensitivity analysis,11-22–11-23slew rate, 11-27second-order biquadratic filtersbiquadratic transfer function,11-11–11-12RC network realization,11-14–11-15single-amplifier low-gainrealization, 11-12–11-13two-amplifier low-gainbiquad configuration,11-14second-order positive-gain filterbandpass circuit, 11-8–11-9high-pass filter, 11-9–11-10low-pass filter, 11-6–11-8notch filter circuits,11-10–11-11second-order transfer functionsbiquadratic transfer function,11-3–11-4high-pass and bandpasstransfer functions, 11-3low-pass filter, 11-2tuning active filters, 11-6Low-pass filters (LPF)analog prototype filtersbilinear transformation,19-26impulse invariant method,19-24–19-251-D analog transfer function2-D zero-phase filter,23-21rotation angle, 23-20–23-21subfilter stability andrealization, 23-201-D discrete transfer function,23-21–23-22digital frequency transformation,19-33