Time Series Analysis Methods in Chemometrics

Recursive structures are introduced for implementing long linear-phase finite impulse response (FIR) filters using a very small number of multipliers. The implementation uses the principle of switching and resetting between two identical copies of the same infinite impulse response (IIR) filter. The impulse response of the resulting filters is a truncated and shifted version of the response of a filter G(z)G(z/sup -1/) where G(z) is a stable IIR stable and G(z/sup -1/) is the corresponding unstable IIR filter. The filters are implemented as a parallel connection of several branches, each branch generating a truncated response corresponding to a complex conjugate pole pair and its mirror-image pair. The truncation is performed using a feedforward term which provides pole-zero cancellations. To stabilize the pole-zero cancellations, and to avoid the quantization error from growing too much, the branch filters are implemented by applying the principle of switching and resetting. It is shown, by means of an example, that by using this approach a nearly optimum FIR filter of order larger than 500 using just 17 adjustable parameters can be designed. >

Filters are used to implement signal transforms, and filter design is a very important part of the signal processing field. There are currently 2 types of filters available: the finite impulse response (FIR) filter, and the infinite impulse response (IIR) filter. While FIR filters have desirable traits such as stability (an absence of poles), IIR filters are able to generate outputs more efficiently. This paper combines the two types of filters by introducing an output slope trigger, to make a hybrid impulse response (HIR) filter with desirable traits from both FIR and IIR filters

One of the main purposes of digital filtering is to improve the quality of the signal. In this chapter, we give an overview of digital filtering. This often uses transformations in order to maintain the desired information in the presence of undesired signals that could corrupt it. Finite Impulse Response (FIR) and Infinite Impulse Response (IIR) filters are linear time invariant filters because the coefficients of the filters do not vary with time (i.e., they are time invariant) as well as because the signal is decomposed into a linear combination of basic signals (i.e., the linearity property). The FIR filter is non-recursive as this does not have feedback. In contrast the IIR filter has a recursive component because of feedback. The application of FIR filters to signal processing is more computationally involved than with IIR filters because FIR needs more coefficients than IIR filters.

Repeaters equipped with on-board digital baseband processing in a time division duplex (TDD) demand short processing time in order to alleviate inter-symbol interference resulting from having a time delay that is greater than the guard time. To accomplish this, the total system delay of the repeater should be minimized as much as possible without distorting signal quality. Conventionally, the finite impulse response (FIR) type of filter is deployed as a channelization filter, but due to the necessity of large numbers of coefficients to fulfill a prerequisite filter response with a sharp transition band characteristic, an unwanted excessive time delay intrinsically occurs. To make the processing delay as low as possible, this paper proposes a method employing a minimum-phase characterized infinite impulse response (IIR) filter whose magnitude response is almost identical to that of the original FIR filter. Furthermore, in order to linearize the phase response of the designed IIR filter, this paper also introduces an all-pass filter cascaded with the IIR filter for digital down-conversion as well as up-conversion. To achieve further simplicity, this paper introduces polyphase-style IIR filters transformed from conventional single IIR filters that have their own all-pass filters in order to linearize the phase response. The computer simulation results verify that the proposed integrated IIR filter exhibits a relatively short processing delay with a minor deterioration in signal quality-like error vector magnitude (EVM) performance.

An algorithm for multichannel adaptive IIR (infinite impulse response) filtering is presented and applied to the active control of broadband random noise in a small reverberant room. Assuming complete knowledge of the primary noise, the theoretically optimal reductions of acoustic energy are initially calculated by means of a frequency-domain model. These results are contrasted with results of a causality constrained theoretical time-domain optimization which are then compared with experimental results, the latter two results showing good agreement. The experimental performances of adaptive multichannel FIR (finite impulse response) and IIR filters are then compared for a four-secondary-source, eight-error microphone active control system, and it is found that for the present application FIR filters are sufficient when the primary noise source is a loudspeaker. Some experiments are then presented with the primary noise field generated by a panel excited by a loudspeaker in an adjoining room. These results show that far better performances are provided by IIR and FIR filters when the primary source has a lightly damped dynamic behavior which the active controller must model.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Time-interleaved analog-to-digital converter (TIADC) mismatch compensation filters are traditionally finite impulse response (FIR) filters. The advantages of using FIR filters are that FIR filters are inherently stable and that the design techniques are readily available. In this paper, we show that, infinite impulse response (IIR) mismatch compensation filters with guaranteed stability can be designed and for the same total number of coefficients, the IIR filters achieve better mismatch compensation than their FIR counterparts. We also show that for a given spurious frequency power, our new IIR TIADC compensation filter yields more than 30% saving in the total number of multiplier coefficients when compared to the conventional FIR TIADC compensation filters.

This paper describes a new approach to the design of multidimensional (M-D) finite-wordlength digital filters with specifications in the frequency and spatial domains. The approach is based on stochastic optimization and extends previous work on finite impulse response (FIR) filters in two ways: by inclusion of spatial constraints and by application to the case of infinite impulse response (IIR) filters. The formulation proposed is based on a multiple-term objective function that, in addition to magnitude constraints, also includes step response, group delay and stability constraints. Our attention to these characteristics stems from the application of such filters to video processing that we are actively pursuing. Since filter coefficients are of finite precision and since the objective function is multivariable, nondifferentiable and likely to have multiple minima, we use simulated annealing for optimization. We show numerous examples of the design of practical filters such as channel and luminance/chrominance separation filters used in the NTSC system. We demonstrate the impact of coefficient precision as well as of group delay and step response constraints on filter parameters. >

In this paper is simulated the time- domain unit sample response of sine function and frequency- domain response of sine function. Digital filter plays an important role in today’s world of communication and computation. Without digital filter we cannot think about proper communication because noise occurs in channel. For removing noise or cancellation of noise we use various type of digital filter. In signal processing, there are mainly two types of filters exist .they are the Finite Impulse Response (FIR) filter and Infinite Impulse Response (IIR) filter. Finite Impulse Response (FIR) filter can be designed form Infinite Impulse Response (IIR) filter by various techniques. The widely used technique is the window technique. This paper low-pass FIR filter is implemented using an efficient adjustable window function based on Hamming window and Blackman window function. The output of the FIR design by Blackman window and the Blackman window are shown in this paper by simulating the code in Matlab. The Matlab program returns with a satisfactory result with proper magnitude plotting.

For multi-track read channel of high areal density magnetic recording systems, two-dimensional (2-D) equalizer is normally considered to shape the readback signal to the desired 2-D generalized partial response (GPR) target. However, the equalizer can correlate the additive noise in the signal and the noise can become the correlated/colored noise which will have a negative impact on the performance of the detector. In the literature, a noise predictive detector using a linear noise predictor (a finite impulse response (FIR) filter) is proposed to tackle the performance loss due to the color/correlated noise. Integrating noise prediction into a detector can grow the complexity of the detector depending on the number of taps in the FIR filter. Alternatively, the noise predictor can also be implemented using an infinite impulse response (IIR) filter. Moreover, IIR predictor can provide the performance gain without requiring a large number of filter's taps. Therefore, in this paper, we study the performance of a noise predictive multi-track joint detector using an IIR filter for the multi-track read channel of high areal density bit-patterned media recording (BPMR) systems. We evaluate its performance against with the multi-track joint detectors with and without conventional noise predictors using FIR filter.

Finite impulse response digital filters

This paper presents a method for the weighted least-squares approximation of finite impulse response (FIR) filters by infinite impulse response (IIR) filters. It is shown, how a solution to this approximation problem can be obtained by solving a related pure least-squares approximation problem. For the latter, we utilize a generalized version of a previously published technique with low computational complexity and guaranteed stability of the IIR filters. Unlike the well-established model-reduction approaches that are carried out in the state space, our method works directly with the numerator and denominator coefficients of the transfer functions. Thus, the influence of finite-precision arithmetic on the results is small. This makes our approach applicable for the approximation of large-order FIR filters and allows the usage of arbitrarily shaped weighting functions. It is shown that our method can successfully be employed to achieve a uniform approximation.

The use of IIR (infinite impulse response) filters for edge detection is studied. IIR filters are shown to perform better than the FIR (finite impulse response) filters for this application. It is also shown that the computational savings in using IIR filters is quite significant.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

The advantage of infinite-impulse response (IIR) filters over finite-impulse response (FIR) ones is that the former require a much lower order (much fewer multipliers and adders) to obtain the desired response specifications. However, in contrast with well-developed FIR filter bank design theory, there is no satisfactory methodology for IIR filter bank design. The well-known IIR filters are mostly derived by rather heuristic techniques, which work in only narrow design classes. The existing deterministic techniques usually lead to too high order IIR filters and thus cannot be practically used. In this paper, we propose a new method to solve the low-order IIR filter bank design, which is based on tractable linear-matrix inequality (LMI) optimization. Our focus is the quadrature mirror filter bank design, although other IIR filter related problems can be treated and solved in a similar way. The viability of our theoretical development is confirmed by extensive simulation.

Digital infinite impulse response (IIR) filter have become the target of growing interest, because they often provide a much better performance and less computational cost than finite impulse response (FIR) filters. Since the problem of error surface of designing Digital IIR filters is generally nonlinear and multimodal, global optimization techniques are required in order to avoid local minima. In this paper, an evolutionary method based on Imperialist Competitive Algorithm (ICA) has been proposed to design Digital IIR filters. By adding a step to the standard ICA algorithm, its performance has been improved in searching solution space and convergence to the global minima. Simulation results show the efficiency of the proposed method to design Digital IIR filter.

The focus of this report is to describe a system for recording surface His-Purkinje and ventricular late potentials on a beat-by-beat basis outside of a shielded environment. An AC magnetic field monitoring device was designed for improved site selection, orientation, and quality control of the acquisition. His-Purkinje signals are detected utilizing spatial averaging and specific channel selection algorithms applied to discriminate random noise from signal. Beat-by-beat vectormagnitude complexes were generated from pairs of X, Y, and Z leads. Both infinite impulse response (IIR) filters, modified for beat-by-beat approaches, and finite impulse response (FIR) filters were utilized. Using the IIR filter, beat-by-beat recordings from test subjects were compared to the signal averaged electrocardiogram (SAECG). Measurement parameters from normal test subjects fell within the previously specified normal range for the SAECG. The IIR filter applied to beat-by-beat recordings exhibited sharp frequency response and a precisely defined cutoff frequency allowing maximal attenuation of the low frequency components in the ST segment. While filter ringing was eliminated, discontinuity and distortion of the filtered waveform resulted. The FIR filter with linear phase response retained the integrity and morphology of the complex but because of its flat frequency response, the ST segment was not as well attenuated and it was more difficult to isolate late potentials. A high order FIR filter should be used if the desire is to match the frequency response of the four-pole IIR filter, since the frequency response of the FIR filter is primarily determined by the order of the filter.(ABSTRACT TRUNCATED AT 250 WORDS)