Digital Finite Impulse Response Research Articles

Use of K-means clustering in migraine detection by using EEG records under flash stimulation

In this study, a new migraine analysis method was proposed by using EEG (electroencephalography) signals under flash stimulation in time domain. EEG signal is one of the most complex biomedical signals due to its complex nature. Therefore, these types of signals are commonly pre-processed before the analysis procedure. Since, pre-processing techniques affect the analysis results positively or negatively, the achievements of these pre-processing techniques are very important. Flash-stimulated and non-stimulated EEG signals obtained from healthy subjects and migraine patients. First, a digital band pass FIR (Finite Impulse Response) filter is used to select beta band of the T5-T3 channel EEG signals. Then a time domain based pre-processing technique, histogram, was employed to obtain the features. Histogram differences in the case of flash stimulation (or non-stimulation) calculated and used as features for the healthy subjects and migraine patients. These features are applied to a k-means clustering algorithm to see clustering results of the proposed technique. Silhoutte clustering results show that, a good clustering performance is evaluated as 86.6% correct clustering rate (CCR) with the used techniques in migraine analysis. Results provide a good insight in this area for future studies. Key words: Migraine, EEG, K-means cluster, histogram.

A nearly optimum linear-phase digital FIR filters design

A new simple method to design linear-phase finite impulse response (FIR) digital filters, based on the steepest-descent optimization method, is presented in this paper. Starting from the specifications of the desired frequency response and a maximum approximation error a nearly optimum digital filter is obtained. Tests have shown that this method is alternative to other traditional ones such as Frequency Sampling and Parks–McClellan, mainly when other than brick wall frequency response is required as a desired frequency response.

Situational Analysis in Real-Time Traffic Systems

The prediction of traffic situations is a vital issue in modern Intelligent Transport Systems (ITS). Particularly the real time detection and proper assessment of incidents may save live and may contribute to keep the transport network available. However, the influence factors of traffic are subject to multi changes; the influence factors are varying traffic demand, weather, seasons, etc. This allows only a very poor performance in real time assessment of traffic situations. This article focuses on the fact that the possible traffic patterns – depicted as time series – vary only very little on each site, representing specific traffic situations or “normal time series”.That the use of intelligent dedicated digital signal processing systems and communication media is in a position to improve the requirement of Real-Time traffic situational analysis in an efficient and effective way. Digital Finite Impulse Response (FIR) filters are used to analyse sensor measurement data in a way that allows an instantaneous assessment about the actual traffic situation and the detection of abnormal behaviour. A FIR filter cascade is used, each filter represents a specific normal time series like working day, weekend day, rain, winter, etc. The representation of each normal time series is achieved by discrete transformation of the normal time series in order to generate its frequency spectrum and by designing a filter structure with a corresponding frequency response.The deployment of the FIR filters can be in Traffic Control Centres with a vast amount of computational power as well as in the controller cabinets of local sensors on the basis of Digital Signal Processors.

Optimal design of periodic test input signals for multivariable impulse response models

AbstractThis paper considers an optimal test input design problem occurring in a control‐relevant, iterative system identification scheme. The optimization is based on minimizing the expected a posteriori closed‐loop error based on the a priori information given by the data already collected. Instead of directly solving the resulting non‐linear optimization to obtain the test input sequences, two different computationally efficient approaches are proposed. The first approach is cast in the frequency domain and we solve for optimal discrete spectra of the periodic signals under some reasonable approximation. The solution can be realized as an input sequence by performing a spectral factorization and implementing the spectral factor as a digital Finite Impulse Response (FIR) filter. A second approach is suggested by reformulating the optimal design problem as a linear matrix inequalities (LMI) problem. The efficacy of these approaches is demonstrated through a numerical example. Copyright © 2010 John Wiley & Sons, Ltd.

An Adaptively Pipelined Mixed Synchronous-Asynchronous Digital FIR Filter Chip Operating at 1.3 Gigahertz

A high-throughput low-latency digital finite impulse response (FIR) filter has been designed for use in partial-response maximum-likelihood (PRML) read channels of modern disk drives. The filter is a hybrid synchronous-asynchronous design. The speed-critical portion of the filter is designed as a high-performance asynchronous pipeline sandwiched between synchronous input and output portions, making it possible for the entire filter to be embedded within a clocked system. A novel feature of the filter is that the degree of pipelining is dynamically variable, depending upon the input data rate. This feature is critical in obtaining a very low filter latency throughout the range of operating frequencies. The filter is a ten-tap six-bit FIR filter, fabricated in a 0.18-μm CMOS process. Resulting chips were fully functional over a wide range of supply voltages, and exhibited throughputs of over 1.3 giga-items/s, and latencies of 2-5 clock cycles. Interestingly, the filter throughput was limited by the synchronous portion of the chip; the internal asynchronous pipeline was estimated to be capable of significantly higher throughputs, around 1.8 giga-items/s. More importantly though, the adaptively pipelined nature of the filter allows it to offer a worst-case latency of only 10 ns, which is half the worst-case latency of the best previously reported comparable fully-synchronous implementation by Rylov et al.

In vivoPerformance Evaluation of Implantable Wireless Neural Signal Transmission System for Brain Machine Interface

A brain-machine interface (BMI) has recently been introduced to research a reliable control of machine from the brain information processing through single neural spikes in motor brain areas for paralyzed individuals. Small, wireless, and implantable BMI system should be developed to decode movement information for classifications of neural activities in the brain. In this paper, we have developed a totally implantable wireless neural signal transmission system (TiWiNets) combined with advanced digital signal processing capable of implementing a high performance BMI system. It consisted of a preamplifier with only 2 operational amplifiers (op-amps) for each channel, wireless bluetooth module (BM), a Labview-based monitor program, and 16 bit-RISC microcontroller. Digital finite impulse response (FIR) band-pass filter based on windowed sinc method was designed to transmit neural signals corresponding to the frequency range of 400 Hz to 1.5 kHz via wireless BM, measuring over −48 dB attenuated in the other frequencies. Less than ±2% error by inputting a sine wave at pass-band frequencies for FIR algorithm test was obtained between simulated and measured FIR results. Because of the powerful digital FIR design, the total dimension could be dramatically reduced to 23×27×4 mm including wireless BM except for battery. The power isolation was built to avoid the effect of radio-frequency interference on the system as well as to protect brain cells from system damage due to excessive power dissipation or external electric leakage. In vivo performance was evaluated in terms of long-term stability and FIR algorithm for 4 months after implantation. Four TiWiNets were implanted into experimental animals’ brains, and single neural signals were recorded and analyzed in real time successfully except for one due to siliconcoated problem. They could control remote target machine by classify neural spike trains based on decoding technology. Thus, we concluded that our study could fulfill in vivo needs to study various single neuron-movement relationships in diverse fields of BMI.

First-order PMD compensation using optical FIR filter

We present a synthesis algorithm to design an optical finite impulse response (FIR) filter for compensating a first-order polarization mode dispersion (PMD) by minimizing the differential group delay (DGD). The desired frequency response was approximated using two widely used methods in designing digital FIR filters: the Fourier series expansion method and the frequency sampling method. A numerical simulation was performed for an eighth-order filter to demonstrate the difference between the two methods. The simulation results produced a sharper cutoff for the Fourier series expansion and higher stopband attenuation for the frequency sampling method. The Fourier series method produced better results in reducing the DGD.

Protection against soft errors in the space environment: A finite impulse response (FIR) filter case study

The problem of radiation is a key issue in Space applications, since it produces several negative effects on digital circuits. Considering the high reliability expected in these systems, many techniques have been proposed to mitigate these effects. However, traditional protection techniques against soft errors, like Triple Modular Redundancy (TMR) or EDAC codes (for example Hamming), normally result in a significant area and power overhead. In this paper we propose a specific technique to protect digital finite impulse response (FIR) filters applying the “system knowledge”. This means to study and use the singularities in their structure in order to provide effective protection with minimal area and power. The results obtained in the experimental process have been compared with the protection offered by TMR and Hamming codes, in order to prove the quality of the proposed solution.

Improving the UWB Pulseshaper Design Using Nonconstant Upper Bounds in Semidefinite Programming

A critical obstacle for ultra-wideband (UWB) communications is conformity to restrictions set on the allowed interference to other wireless devices. To this end, UWB signals have to comply with stringent constraints on their emitted power, defined by the Federal Communications Commission spectral mask. Different UWB pulseshaper designs have been studied to meet the spectral mask, out of which an approach based on digital finite impulse response filter design via semidefinite programming has stood out. However, so far this approach has assumed an ideal basic analog pulse to use piece-wise constant constraints for the digital filter design. Since any practical analog pulse does not have a flat spectrum, using piece-wise constant constraints leads to considerable power loss. Avoiding such a loss has motivated us to implement the exact constraints through nonconstant piece-wise continuous bounds. Relative to the design assuming an ideal basic analog pulse, our design examples show that the transmission power can be enhanced considerably while obeying the spectral mask. Such an improvement comes with no extra cost of implementation complexity.

Fast algorithms for designing variable FIR notch filters

AbstractThe paper presents fast algorithms for designing finite impulse response (FIR) notch filters. The aim is to design a digital FIR notch filter so that the magnitude of the filter has a deep notch at a specified frequency, and as the notch frequency changes, the filter coefficients should be able to track the notch fast in real time. The filter design problem is first converted into a convex optimization problem in the autocorrelation domain. The frequency response of the autocorrelation of the filter impulse response is compared with the desired filter response and the integral square error is minimized with respect to the unknown autocorrelation coefficients. Spectral factorization is used to calculate the coefficients of the filter. In the optimization process, the computational advantage is obtained by exploiting the structure of the Hessian matrix which consists of a Toeplitz plus a Hankel matrix. Two methods have been used for solving the Toeplitz‐plus‐Hankel system of equations. In the first method, the computational time is reduced by using Block–Levinson's recursion for solving the Toeplitz‐plus‐Hankel system of matrices. In the second method, the conjugate gradient method with different preconditioners is used to solve the system. Comparative studies demonstrate the computational advantages of the latter. Both these algorithms have been used to obtain the autocorrelation coefficients of notch filters with different orders. The original filter coefficients are found by spectral factorization and each of these filters have been tested for filtering synthetic as well as real‐life signals. Copyright © 2007 John Wiley & Sons, Ltd.

Noise Cancellation Signal Processing Method and Computer System for Improved Real-Time Electrocardiogram Artifact Correction During MRI Data Acquisition

A system was developed for real-time electrocardiogram (ECG) analysis and artifact correction during magnetic resonance (MR) scanning, to improve patient monitoring and triggering of MR data acquisitions. Based on the assumption that artifact production by magnetic field gradient switching represents a linear time invariant process, a noise cancellation (NC) method is applied to ECG artifact linear prediction. This linear prediction is performed using a digital finite impulse response (FIR) matrix, that is computed employing ECG and gradient waveforms recorded during a training scan. The FIR filters are used during further scanning to predict artifacts by convolution of the gradient waveforms. Subtracting the artifacts from the raw ECG signal produces the correction with minimal delay. Validation of the system was performed both off-line, using prerecorded signals, and under actual examination conditions. The method is implemented using a specially designed Signal Analyzer and Event Controller (SAEC) computer and electronics. Real-time operation was demonstrated at 1 kHz with a delay of only 1 ms introduced by the processing. The system opens the possibility of automatic monitoring algorithms for electrophysiological signals in the MR environment.

Vibration suppression of structures with densely spaced modes using maximally robust minimum delay digital finite impulse response filters

Due to the inherent flexibility of engineering structures, transient and residual vibrations occur when a motion command is applied, thus raising several practical restrictions concerning their fast, accurate and safe motion. Although various command-preconditioning techniques have been proposed for the effective suppression of the excited vibrations, their application has been limited only to structures with a few distinct and well-separated modes. This paper further considers the applicability of motion preconditioning methods for a large class of lightweight flexible structures, which present multiple densely spaced natural modes, existing even at relatively low frequencies. Properly designed finite impulse response (FIR) filters can lead to an effective motion preconditioning method, suppressing drastically the excited vibrations over the entire excited frequency band. Compared to other alternative preconditioning methods, such as input shapers or infinite impulse response (IIR) filters, FIR filters present the most efficient behavior in terms of vibration suppression efficiency, or in terms of the delay introduced in the motion command, as verified by numerical simulations and experimental results involving multibay trusses, with tenths of densely spaced modes in a range from 0.4 Hz up to 75 Hz.

Design of Digital FIR Filters Using Differential Evolution Algorithm

The differential evolution (DE) algorithm is a new heuristic approach with three main advantages: it finds the true global minimum of a multimodal search space regardless of the initial parameter values, it has fast convergence, and it uses only a few control parameters. The DE algorithm, which has been proposed particularly for numeric optimization problems, is a population-based algorithm like the genetic algorithms and uses similar operators: crossover, mutation, and selection. In this work, the DE algorithm has been applied to the design of digital finite impulse response filters, and its performance has been compared to that of the genetic algorithm and least squares method.

Design techniques for high-speed multirate multistage FIR digital filters

This paper presents architecture design techniques for implementing both single-rate and multirate high-speed finite impulse response (FIR) digital filters, with emphasis on the multirate multistage interpolated FIR (IFIR) digital filters. Well-known techniques to achieve high-speed and low-power applications for the single-rate digital FIR architecture are summarized, followed by the introduction of variable filter order selection, optimal filter decomposition, memory-saving and mirror symmetric filter pairs techniques which offer further gains in both performance and complexity reduction for the multirate multistage digital FIR architecture. A filter design example with TSMC 0.25 µm standard cell for 64-QAM baseband demodulator shows that the area is reduced by 39% for low-complexity application. Moreover, for high-speed application, the chip can operate at 714 MHz. Finally, a designed decimator which is used in the CDMA cellular shows that the area is reduced by 70% as compared with conventional approach.

A hybrid genetic algorithm for the design of FIR filters with SPoT coefficients

An efficient way to reduce complexities and power in the implementation of digital finite impulse response (FIR) filters is to design the filters with coefficients restricted to the sum of signed powers-of-two (SPoT) terms. The design of SPoT-based FIR filters can be formulated as a non-linear optimization problem. Premature convergence and unacceptable computational cost are the major difficulties when conventional optimization algorithms are utilized in SpoT-based FIR filter design. To address the problem, a hybrid genetic algorithm (GST) is proposed in this paper. The hybrid scheme is formed by integrating the main features of an adaptive genetic algorithm (AGA), simulated annealing (SA) and tabu search algorithms. AGA with varying population size and varying probabilities of genetic operations is used as the basis of the hybrid algorithm. SA comes to the picture when it is indicated that AGA may get stuck in a local optimum. The use of SA is to help AGA escape from local optima and prevent premature convergence. The concept of tabu is introduced to increase convergence speed by reducing search space according to the properties of filters coefficients. It is shown by means of examples that the normalized peak ripples of filters can be largely reduced with the help of the proposed algorithm. Compared with other genetic algorithm, GST achieves not only the improved solution quality but also the considerable reduction of computational effort.

Optical networks research at UCL

New dynamic optical switching technologies and adaptive transmission techniques will allow increased capacity and flexibility in future core and metro networks. The Optical Networks Group at UCL has carried out research focused on these areas, in collaboration with industry and other university research groups, for over a decade. In this paper, the technical challenges to be overcome in implementing dynamic, high-capacity networks are discussed, and recent results of the group's work are presented. New network architectures based on wavelength-routing and optical burst switching have been proposed and analysed, and the experimental demonstration of burst switching using fast wavelength-tunable lasers is described. High-capacity dense wavelength division multiplexed transmission systems, using advanced regeneration and equalisation techniques, have been studied, both theoretically, and experimentally using a dynamically reconfigurable recirculating fibre loop. Research results on advanced optical signal formats, all-optical 3R regeneration at 40 Gbit/s channel rates, adaptive analogue and digital electronic processing techniques and optical finite impulse response equalisation are presented. Finally, the development of optical performance monitoring technology, a key component of future all-optical networks, is described. The paper concludes with a prediction of future trends in optical communications research.

A low voltage W-CDMA polar transmitter with digital envelope path gain compensation

This letter presents a polar transmitter using a dual-phase pulsewidth-modulated buck converter with a 50-MHz effective switching frequency. Using a wideband code division multiple access voice signal, the overall system can achieve 52.8% drain efficiency (49.8% power added efficiency) at 24-dBm output power at 836.5MHz with a 3.5-V supply voltage, while passing both adjacent channel leakage power ratio (ACLR1) and alternate channel leakage power (ACLR2) specifications. A digital finite impulse response filter is included in the envelope path to compensate for gain roll-off at higher baseband frequencies. This envelope path compensation allows greater linear bandwidth to be achieved at lower switching frequencies, thus boosting efficiency, and improving ACLR by as much as 8dB. The polar transmitter is characterized over a supply voltage of 2.5-4.5V, making it well suited for battery powered, handheld applications

Optimal waveform design for UWB radios

With transmit power spectra strictly limited by regulatory spectral masks, the emerging ultra-wideband (UWB) communication systems call for judicious pulse shape design in order to achieve optimal spectrum utilization, spectral mask compatibility, and coexistence with other wireless services. Meanwhile, orthogonal pulse sets are often desired in order to apply high-rate multidimensional modulation and (carrier-free) orthogonal frequency-division multiple access. Motivated by these considerations, we suggest a digital finite impulse response (FIR) filter approach to synthesizing UWB pulses and propose filter design techniques by which optimal waveforms that satisfy the spectral mask can be efficiently obtained. For single pulse design, we develop a convex formulation for the design of the FIR filter coefficients that maximize the spectrum utilization efficiency in terms of both the bandwidth and power allowed by the spectral mask. For orthogonal pulse design, a sequential strategy is derived to formulate the overall pulse design problem as a set of convex subproblems, which are then solved in a sequential manner to yield a set of mutually orthogonal pulses. Our design techniques not only provide waveforms with high spectrum utilization and guaranteed spectral mask compliance but also permit simple modifications that can accommodate several other system objectives.

Digital Laguerre filter design with maximum passband-to-stopband energy ratio subject to peak and Group delay constraints

In this paper, we formulate a general design of transversal filter structures with maximum relative passband-to-stopband energy ratio subject to complex frequency response constraints in the passband and the stopband as well as additional constraints such as null constraints. These null constraints are important for applications where the suppression of noise at certain frequencies are important. Additional constraints are introduced allowing approximately linear phase and constant group delay in the passband. For a given set of basis functions, the design problem can be formulated as a semi-infinite quadratic optimization problem in the filter coefficients, which are the decision variables to be optimized. In this paper, we focus on the design of digital Laguerre filter and digital finite impulse response (FIR) filter structures. A modified bridging algorithm is developed for searching for the optimum pole of the Laguerre filters. Design examples are given to demonstrate the effectiveness of the proposed algorithm.

Optimal design of complex FIR filters with arbitrary magnitude and group delay responses

This paper presents a method for the frequency-domain design of digital finite impulse response filters with arbitrary magnitude and group delay responses. The method can deal with both the equiripple design problem and the peak constrained least squares (PCLS) design problem. Consequently, the method can also be applied to the equiripple passbands and PCLS stopbands design problem as a special case of the PCLS design. Both the equiripple and the PCLS design problems are converted into weighted least squares optimization problems. They are then solved iteratively with appropriately updated error weighting functions. A novel scheme for updating the error weighting function is developed to incorporate the design requirements. Design examples are included in order to compare the performance of the filters designed using the proposed scheme and several other existing methods.