Hilbert transformers are one of the very important special classes of finite impulse response (FIR) filters used in signal processing applications. A method is presented to synthesize Hilbert transformers by using wideband linear-phase FIR filters with a piecewise-polynomial-sinusoidal impulse response. The proposed method is based on merging the earlier synthesis scheme proposed by the authors with the method proposed by Chu and Burrus and by modifying it by using an arbitrary number of separately generated center coefficients instead of none used in the method by Chu-Burrus. The desired impulse response is created by using a parallel connection of several filter branches and by adding an arbitrary number of center coefficients to form it. The arithmetic complexity of these filters is proportional to the number of branches, the common polynomial order for each branch and the number of separate center coefficients. The filter coefficients are optimized by using linear programming. An example shows the benefits of these filters compared to the frequency-response masking approach (FRM) with regard to reducing the number of coefficients as well as arithmetic complexity.

A method is presented to synthesize wideband linear-phase FIR filters with a piecewise-polynomial-sinusoidal impulse response. The proposed method is based on merging the earlier synthesis scheme proposed by the authors with the method proposed by Chu and Burrus and by modifying it by using an arbitrary number of separately generated center coefficients instead of only one used in the method by Chu-Burrus. The desired impulse response is created by using a parallel connection of several filter branches and by adding an arbitrary number of center coefficients to form it. The arithmetic complexity of these filters is proportional to the number of branches, the common polynomial order for each branch, the number of separate center coefficients, and the number of complex multipliers. The filter coefficients are optimized by using linear programming. An example shows the benefits of these filters with regard to reducing the number of coefficients as well as the arithmetic complexity.

Two computationally efficient structures to design and implement linear-phase narrowband FIR filters with a symmetrical piecewise-polynomial impulse response have been proposed by Saramaki and Mitra. The efficiency of these structures is based on implementing the overall transfer function as a parallel connection of a few branches of the form Gl(zL)Fl(z), where each Fl(z) requires no real multipliers. These structures have been generated in an ad-hoc manner. This paper introduces straightforward approaches to generate such Fl(z)s for both structures

We introduce a genetic algorithm (GA)-based method for structural optimization of multiplicative general parameter (MGP) finite impulse response (FIR) filters. These computationally efficient reduced-rank adaptive filters are robust, suitable for predictive configurations, and they have numerous applications in 50/60 Hz power systems instrumentation. The design process of such filters has three independent stages: Lagrange multipliers-based optimization of the sinusoid-predictive basis filter, genetic algorithm-based search of optimal FIR tap cross-connections and, finally, the online MGP-adaptation phase guided by variations in signal statistics. Thus, our multi-stage design procedure is a complementary fusion of hard computing (HC) and soft computing (SC) methodologies. Such advantageous fusion (or symbiosis) thinking is emerging among researchers and practicing engineers, and it can potentially lead to competitive combinations of individual HC and SC methods.

We introduce an evolutionary programming based method for designing robust and computationally efficient adaptive bandpass filters. These predictive filters are optimized for generating current references in active power filters (APFs). The accuracy (phase/amplitude) of the reference current is crucial in current injection type systems, because it directly affects the harmonics reduction ability of the APF. Our digital filtering approach has the following advantages: selective bandpass response, efficient attenuation of specific harmonic components, capability to handle typical frequency alteration, small number of multiplications, and structural simplicity. In an illustrative example, the total harmonic distortion of an artificial current waveform was reduced from 36.7% to less than 3.7% within the line frequency range 49-51 Hz. The proposed scheme is a combination of the hard computing (HC) type multiplicative general parameter method and evolutionary programming that is a constituent of soft computing (SC). Such fusion thinking is emerging among researchers and engineers, and it can potentially lead to efficient combinations of HC and SC methodologies - both on the algorithm level and on the system level.

A class of computationally efficient adaptive algorithms for transversal filters is discussed. The algorithms, which are based on the so-called general parameter method, use typically one or a few dynamically adjusted parameters, each to be added to a block of coefficients of a fixed basis FIR filter. Thus the overall filter is adapted so that the output error is minimized. The adaptive extension can be constructed as an 'add-on' element to be used in parallel with fixed-coefficient filters. An efficient implementation structure is proposed, and the stability and convergence properties of the multiple-parameter algorithm are analyzed.

A simple heuristic method for designing frequency-selective finite impulse response (FIR) filters with prediction properties is presented. Starting from passband and stopband specifications, a linear-phase model filter is converted into a minimum phase equivalent and the zero locations are manipulated in order to achieve negative group delay at the zero frequency. The method allows us to design FIR ramp predictors with nearly equiripple stopband characteristics.

A design environment is presented, which makes it possible to design and implement efficiently application specific sigma-delta A/D converters. Several design methods and developed algorithms and programs are presented, which allow one to analyse, design, and optimize modulators and decimation filters at every design step towards silicon. The design and implementation of a high-speed, low-voltage, multibit sigma-delta modulator, and a digital decimation filter for GSM application are used as examples.

Differentiation by means of digital signal processing is needed for estimating the rate of change or slope of digitized signals in many motion control and automation applications, including acceleration measurement. Since the ideal differentiator is unrealizable, several kinds of approximations have been proposed in the literature. In this work, we propose a digital differentiation scheme which is flexible and in many cases avoids the unfavourable noise properties of wideband approximation approaches. This is achieved by cascading an integrator and a FIR filter in an adaptive loop such that the filter adapts as an application-specific differentiator. Examples of operation with different signal classes are given, including piecewise polynomials, frequently encountered in motion control applications.

A new method to enhance the quality of a telephone connection by suppressing noise and disturbances in speech signals is presented. As the noise is evenly spread over the entire signal band, a nonlinear filtering algorithm is required to improve the signal-to-noise-ratio. The system is being realized as an analog full custom ASIC using switched capacitor (SC)-substructures and CMOS-technology. The advantages of the analog implementation include low power consumption, small integration area and inexpensiveness of the chip. In this paper, the noise suppression algorithm is described and the SC-circuit implementation is presented.