Digital Filter Designs for Recursive Frequency Analysis

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 authors propose pole controlled infinite impulse response (IIR) adaptive digital filters (ADFs) and show their pole controllability with trajectories of poles on the MSE (mean square error) surface. The proposed IIR ADF consists of an FIR (finite impulse response) part and an IIR part. The FIR part identifies flat delay and responses of the echo which comes from poles near the origin of the z-plane. The IIR part consists of several second-order IIR filters connected in parallel. The filter sections are able to operate mutually independently. This type of IIR ADF has no stability problem in controlling the pole location, since the ADF consists of stable biquad sections or second-order IIR sections. Simulation results show that the proposed IIR ADF has excellent pole controllability. >

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.

The well-known advantages of pipelining as applied to Finite Impulse Response (FIR) Residue Number System (RNS) arithmetic digital filters is extended to the important area of Infinite Impulse Response (IIR) digital filters through a new technique based on augmentation of the IIR transfer function. Through this technique, pipelined IIR filters based on RNS Read-Only-Memory (ROM) table look-up techniques can be designed which offer throughput rates equal to the table look-up time of the ROM's. This high-speed realization can be achieved even though the recursive filter algorithm requires multiple delays in realizing the output of the filter. For the example of a typical second-order IIR filter, the pipelined structure represents a five-fold increase in speed over standard techniques. Higher order realizations will yield proportionately higher speed improvements. Although the new technique does increase somewhat the hardware complexity of the filter, the increase in speed will often justify the additional hardware. The paper discusses the basic technique, stability considerations, and hardware realizations.

A recently developed adaptive IIR (infinite impulse response) filtering algorithm is used to implement an adaptive IIR echo canceller. The simplicity and the proved convergence of the algorithm make it attractive for this application. The advantages in using the adaptive IIR echo canceller are discussed as well as some remaining problems. Extensive computer simulations show that the IIR canceller performs better than the FIR (finite impulse response) canceller after convergence, although in general the IIR canceller converges more slowly. It is also observed that the order selection of the IIR canceller is crucial in achieving superior performance over FIR cancellers. >

Perfect linear-phase two-channel QMF banks require the use of finite impulse response (FIR) analysis and synthesis filters. Although they are less expensive and yield superior stopband characteristics, perfect linear phase cannot be achieved with stable infinite impulse response (IIR) filters. Thus, IIR designs usually incorporate a postprocessing equalizer that is optimized to reduce the phase distortion of the entire filter bank. However, the analysis and synthesis filters of such an IIR filter bank are not linear phase. In this paper, a computationally simple method to obtain IIR analysis and synthesis filters that possess negligible phase distortion is presented. The method is based on first applying the balanced reduction procedure to obtain nearly allpass IIR polyphase components and then approximating these with perfect allpass IIR polyphase components. The resulting IIR designs already have only negligible phase distortion. However, if required, further improvement may be achieved through optimization of the filter parameters. For this purpose, a suitable objective function is presented. Bounds for the magnitude and phase errors of the designs are also derived. Design examples indicate that the derived IIR filter banks are more efficient in terms of computational complexity than the FIR prototypes and perfect reconstruction FIR filter banks. Although the PR FIR filter banks when implemented with the one-multiplier lattice structure and IIR filter banks are comparable in terms of computational complexity, the former is very sensitive to coefficient quantization effects.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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. >

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.

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.

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

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.

This paper is on the use and performance of M-path polyphase Infinite Impulse Response (IIR) filters for channelisation, conventionally where Finite Impulse Response (FIR) filters are preferred. This paper specifically focuses on the Discrete Fourier Transform (DFT) modulated filter banks, which are known to be an efficient choice for channelisation in communication systems. In this paper, the low-pass prototype filter for the DFT filter bank has been implemented using an M-path polyphase IIR filter and we show that the spikes present at the stopband can be avoided by making use of the guardbands between narrowband channels. It will be shown that the channelisation performance will not be affected when polyphase IIR filters are employed instead of their counterparts derived from FIR prototype filters. Detailed complexity and performance analysis of the proposed use will be given in this article.

An efficient transformation method for the realization of a delayed multipath two-dimensional IIR (infinite impulse response) digital filter is presented. Although the structure does not give 100% multiprocessing efficiency, the maximum overall throughput improvement that can be achieved is high. The delayed multipath structure has been successfully applied to the realization of an FIR (finite impulse response) digital filter. In actual implementation, the method involves difficulty when applied directly to an IIR digital filter because of the inherent timing constraint in the recursive loop. With the transformation method, extra loop delay is allowed in the recursive part of the multipath structure. Consequently, the problem of inherent timing constraint in the recursive loop is solved. Furthermore, the transformation method is efficient in terms of computational complexity, throughput improvement, and multiprocessing efficiency.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

This paper presents a high performance frequency domain filter implementation for a moving window-type processing. The computational structure consists of three stages: a sliding discrete Fourier transform (SDFT) for a vectorized updating of the DFT; a frequency domain filter; and a one-point inverse discrete Fourier transform (IDFT). The total computation required for generating one filtered output point is 2/spl times/N multiplications (N is the frequency window length) and 3/spl times/N additions compared to 2/spl times/N/spl times/log/sub 2/N multiplications and additions if using FFT and IFFT. The proposed structure also has the advantage of being parallel in nature and can be used in various real-time frequency processing, continuous data flow, single or multiple channel applications.

In this paper a new method of neural filtering using artificial neural network systems is presented for the filtering problems of linear and nonlinear, stationary and nonstationary stochastic signals. The neural filter (denoted neurofilter) developed in this paper has either finite impulse response (FIR) structure or infinite impulse response (IIR) structure. The neurofilter differs from the conventional linear digital FIR and IIR filters because the artificial neural network system used in the neurofilter has a nonlinear structure due to the sigmoid function. Numerical studies for the estimation of a second-order Butterworth process are performed by changing the structures of the neurofilter in order to evaluate the performance indices under changes of the output noises or disturbances. The results obtained from these studies verified the capabilities which are essentially necessary for on-line filtering of various stochastic signals.