Low Power Fir Digital Filter

This paper considers the problem of change-point detection for noisy data. Estimation of signal frequency content relies on differential algebra and non-commutative algebra together with operational calculus. We adapt this approach to the study of changes that may be ...

➢ Automatically detect noise and cutoff frequencies from an audio file. ➢ Apply frequency domain filtering using FFT. ➢ Enhance audio quality by removing high-frequency noise. ➢ Visualize frequency components before and after filtering. ➢ Save the filtered audio and provide a user-friendly interface. Concepts Used: Sampling Rate (fs): Number of samples per second in the audio signal. Fast Fourier Transform (FFT): Algorithm to convert a signal from the time domain to the frequency domain. Magnitude Spectrum: The absolute value of the FFT output, representing amplitude at each frequency.

When digital filters are designed with power-of-two coefficients, the multiplications can be implemented by simple shifting operations. In this paper, the genetic algorithm (GA) is used to design 2-D multiplierless filters. The 2-D filter is designed to have periodically shift variant (PSV) coefficients. This increases the degress of freedom for the multiplierless coefficients so that a better approximation can be achieved. The design involves finding the impulse response of the 2-D PSV filter in closed form and then using the GA to find the filter coefficients. Two different types of GA are used, namely, the Binary-GA and the Integer-GA. Some design examples are presented to illustrate the concepts.

A novel algorithm for designing low-power and hardware-efficient linear-phase finite-impulse response (FIR) filters is presented. The algorithm finds filter coefficients with reduced number of signed-power-of-two (SPT) terms given the filter frequency response characteristics. The algorithm is a branch-and-bound-based algorithm that fixes a coefficient to a certain value. The value is determined by finding the boundary values of the coefficient using linear programming. Although the worst case run time of the algorithm is exponential, its capability to find appreciably good solutions in a reasonable amount of time makes it a desirable CAD tool for designing low-power and hardware-efficient filters. The superiority of the algorithm on existing methods in terms of SPT term count, design time, hardware complexity, and power performance is shown with several design examples. Up to 30% reduction in the number of SPT terms is achieved over unoptimized Remez coefficients, which is 20% better than compared optimization methods. The average power saving is 20% over unoptimized coefficients, which is up to 14% better than optimized coefficients obtained with existing methods. filter design, FIR digital filters, linear programming, multiplierless design, power-of-two coefficients. C ONSTANT coefficient finite-impulse-response (FIR) digital filters can be realized in parallel using as many multipliers as the number of coefficients in the filter. However, since multipliers are power-and area-consuming circuits, it is a common practice to first represent coefficients as sums of signed-power-of-two (SPT) terms and then replace the multipliers by shift and add circuits. From the power perspective, the fewer the number of adders, the less power the filter will consume. The number of adders depends on the number of nonzero bits (SPT terms) of the quantized coefficients. A practical way to provide reduced SPT terms is to use canonic signed digit (CSD) representation since it offers fewer SPT terms in the representation than two's complement representation. Methods proposed in the literature in general consider the reduction of hardware cost; however, they serve as a basis for Manuscript

Many applications of finite impulse response (FIR) digital filters impose strict format constraints for the filter coefficients. Such requirements increase the complexity of determining optimal designs for the problem at hand. We introduce a fast and efficient method, based on the computation of good nodes for polynomial interpolation and Euclidean lattice basis reduction. Experiments show that it returns quasi-optimal finite wordlength FIR filters; compared to previous approaches it also scales remarkably well (length 125 filters are treated in < 9s). It also proves useful for accelerating the determination of optimal finite wordlength FIR filters.

Fully serial multipliers can play an important role in the implementation of DSP algorithms in resource-limited chips such as FPGAs; offering area efficient architectures with a reduced pin count and moderate throughput rates. In this paper two structures that implement the fully serial multiplication operation are presented. One significant aspect of the new designs is that they are systolic and require near communication links only. They are superior in speed and area usage to similar architectures in the literature. The paper also present a new fully serial multiplier optimized for area-time 2 efficiency with better performance than available architectures in the open literature.

Digital signal processing is most widely used to process the signal. In digital signal processing filters are used to remove some unwanted constituents from aspired signal. Windowing is a scheme of finite impulse response filters. Present paper proposes a new versatile window function. It has two variable parameters first one is window span N and another changeable parameter is r. when the value of variable parameter r increases width of major lobe of window also increases with better side lobe reduction and vice versa. Gaussian window and Kaiser window are the well-known variable windows. This paper shows that the proposed window has more desirable results in comparison of Gaussian and Kaiser window with low power loss and better side lobe reduction. To achieve minimum power loss peak side lobe level should have to minimum. Proposed window has low peak side lobe level (-17.681dB) in comparison of Gaussian (-11.836dB) and Kaiser window (-6.9704dB). Proposed work shows that the propo...

This book is intended for a 1-year undergraduate or first-year graduate course in traditional digital filter design for linear systems. The authors' ideal class would be a mixture of students from the physical sciences. They recommend some mathematical sophistication at the advanced calculus level and some computer programming experience in FORTRAN-77. The authors make no claim for completeness, but strive for a self-contained treatment. This second edition contains revisions to the chapters on discrete transforms, finite-impulse response (FIR), and infinite impulse response (IIR) filtering, and spectral estimation. New chapters have been added on the z transform and least-squares system design. Lattice structures, parametric spectral estimation, and new computer programs have also been added. The authors identify and exploit the similarity between digital and continuous signal processing methods in the analysis of time series. They apply this theme throughout the book with comparisons between digital and analog methods noted frequently. In fact, the synthesis of continuous signals using digital methods is discussed at length. The contents of Digital Signal Analysis include a forward by R. W.

For extracting the individual channels from input signal of wideband, Software Radio Channelizer was often used on multi-standard wireless communication. Despite the effective channelizer design that decreases the complexity of computational, delay and power consumption is challenging. Thus, to promote the effectiveness of the channelizer, we have provided the Non-Maximally Coefficient Symmetry Multirate Filter Bank. For this, a sharp wideband channelizer is designed to be using the latest class of masking responses with Non-maximally Decimated Polyphase Filter. Moreover, coefficient symmetry is incorporated into the Non-Maximally Coefficient Symmetry Multirate Filter Bank to improve the hardware efficiency and functionality of the proposed schemes. To prove the complexity enhancement of the proposed system, the design is analyzed with communication standard with existing methods.

In both digital filter design and spectral estimation, the choice of a windowing function can play an important role in determining the quality of overall results. The main role of the window is to damp out the effects of the Gibbs phenomenon that results from truncation of an infinite series. There are various types of window techniques. In many applications like filter design, FFT, beam forming, signal processing and measurements it is seen that particular one type of filter is not applicable for all purpose. This paper presents a new window technique which has better performance compared to commonly used window like Hamming, Hanning & Blackman window. The simulation result where the advantage of this proposed window is shown is actually the minimization of side lobes& ripples. The simulation is done in Matlab 12. The Matlab program returns with a satisfactory result with proper magnitude plotting& filter response.

This paper presents the application of Moth Flame optimization (MFO) algorithm to determine the best impulse response coefficients of FIR low pass, high pass, band pass and band stop filters. MFO was inspired by observing the navigation strategy of moths in nature called transverse orientation composed of three mathematical sub-models. The performance of the proposed technique was compared to those of other well-known high performing optimization techniques like techniques like Particle Swarm Optimization (PSO), Novel Particle Swarm Optimization (NPSO), Improved Novel Particle Swarm Optimization (INPSO), Genetic Algorithm (GA), Parks and McClellan (PM) Algorithm. The performances of the MFO based designed optimized FIR filters have proved to be superior as compared to those obtained by PSO, NPSO, INPSO, GA, and PM Algorithm. Simulation results indicated that the maximum stop band ripples 0.057326, transition width 0.079 and fitness value 1.3682 obtained by MFO is better than that of...