Blind Deconvolution in Nonminimum Phase Systems Using Cascade Structure

PurposeTraditionally, each time a new design for a finite impulse response (FIR) filter is required, a new algorithm has to be developed specially for the FIR filter. Furthermore, corresponding hardware architecture must be designed specially to meet the requirement of the FIR specifications. The purpose of this paper is to propose an arithmetic logic unit (ALU)‐based universal FIR filter suitable for realization in field programmable gate arrays (FPGA), where various FIR filters can be implemented just by programming instructions in the ROM with identical hardware architecture.Design/methodology/approachRather than multiplier‐accumulator‐based architecture for conventional FIR, the proposed ALU architecture implements the FIR functions by using accumulators and shift‐registers controlled by the instructions of ROM. Furthermore, time division multiplexing access (TDMA) technique is employed to reduce the chip size. In addition, the proposed FIR architecture is verified in a SOC hardware and/or software co‐emulation system.FindingsAn ALU‐based universal FIR filter suitable for realization in FPGA is designed and verified in a SOC hardware/software co‐emulation system with example of a 64‐tap FIR filter design.Originality/valueA software‐based design method as well as TDMA scheme for the ALU‐based FIR filter are introduced, making FIR filter architecture universal, programmable, and consuming less FPGA resources.

Digital filters play a central role in modern Digital Signal Processing (DSP) systems. Finite Impulse Response (FIR) filters can provide solutions with guaranteed stability and linear phase. However, the main disadvantage of conventional FIR filter designs is that they become computationally complex, especially in applications demanding narrow transition bandwidths. Therefore, designing FIR filters with very stringent specifications and a low complexity is currently an important challenge. In this chapter, a review of the recent methods to efficiently design low-complexity linear-phase FIR filters is presented. The chapter starts with an introduction to linear-phase FIR digital filters. Then, an overview of the design methods that have been developed in literature to design low-complexity FIR filters is presented. Finally, the most common and recent of these methods along with their corresponding special structures are explained.

Digital filters play a central role in modern digital signal processing (DSP) systems. Finite impulse response (FIR) filters can provide solutions with guaranteed stability and linear phase. However, the main disadvantage of conventional FIR filter designs is that they become computationally complex, especially in applications demanding narrow transition bandwidths. Therefore, designing FIR filters with very stringent specifications and a low complexity is currently an important challenge. In this chapter, a review of the recent methods to efficiently design low-complexity linear-phase FIR filters is presented. The chapter starts with an introduction to linear-phase FIR digital filters. Then, an overview of the design methods that have been developed in literature to design low-complexity FIR filters is presented. Finally, the most common and recent of these methods along with their corresponding special structures are explained.

In Digital wireless communication system Finite Impulse Response (FIR) filter is used fundamentally pipelined as well as support Multiplication with Accumulation scheme (MAC) that results in important save of calculation. Efficient area along with delay recognition of great order FIR filters for update applications have been achieved by the opportunity of recognition of block FIR filter in transpose form organization. The projected transpose form block filter of update applications are developed by a general carry select adder based architecture. Secured digital FIR filter block is implemented by a pepped-up design using the MAC scheme. Booth multiplier has been used in MAC scheme. The proposed method has less area also delay than conventional filter.

Background/Objectives: FIR filters play a vital role in signal processing applications. This research work presents a low power and high speed efficient buffer based Distributed Algorithms and it is analyzed with Electro Cardio Gram (ECG) signal Finite Impulse Response (FIR) filter design. Methods/Statistical Analysis: The proposed FIR filter is designed using buffer based DA and it is simulated and synthesized using Cadence digital labs. This is compared with different architectures such as conventional DA, separated look up table DA and LUT less DA. Findings: Synthesis report shows that the proposed design has 52% less power dissipation compared with the conventional DA, 21% reduction in delay with separated Look Up Table (LUT) DA and 8% reduction in area with LUT less DA. Conclusion/Improvements: Presently this method is applied for ECG signal input with 16-tap FIR filter. This can be extended for higher order filters to achieve better performance.

Fractional sample interpolation with finite impulse response (FIR) filters is commonly used for motion-compensated prediction (MCP). The FIR filtering can be viewed as a signal decomposition using restricted basis functions. The concept of generalized interpolation provides a greater degree of freedom for selecting basis functions. We developed a generalized interpolation framework for MCP using fixed-point infinite impulse response and FIR filters. An efficient multiplication-free design of the algorithm that is suited for hardware implementation is shown. A detailed analysis of average and worst case complexities compared to FIR filter-based interpolation techniques is provided. Average bitrate savings of around 2.0% compared to an 8-tap FIR filter are observed over the high-efficiency video coding dataset at a similar worst case complexity.

WITHDRAWN: An Optimistic Design of 16-Tap FIR Filter with Radix-4 Booth Multiplier Using Improved Booth Recoding Algorithm

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.

Nowadays, the communications and computations has been performed by Digital Finite Impulse Response (FIR) filter. FIR filter is predominantly used in DSP applications for efficient implementations. FIR filter is able to declare a firm linear phase frequency characteristic with any type of amplitude frequency characteristic in a DSP system. A reconfigurable FIR filter architecture has been implemented using Least Mean Square (LMS) algorithm in the proposed scheme. The proposed scheme achieves better performance when compared to an existing scheme. The proposed method has been implemented in ModelSim tool and efficiency has been calculated by using the device Virtex 6 Low Power in Xilinx ISE Design Suite 12.4.

Digital filter is an important fundamental component in digital signal processing (DSP) systems. Among the digital filters, the finite impulse response (FIR) filter is one of the most commonly used schemes. As a low-complexity hardware implementation technique, stochastic computing has been applied to overcome the huge hardware cost problem of high-order FIR filters. However, the stochastic FIR filter (SFIR) scheme suffers from long processing latency and accuracy degradation. In this paper, the bit stream representation noise is theoretically analyzed, and an adaptive scaling algorithm (ASA) is proposed to improve the accuracy of SFIR with the same bit stream length. Furthermore, a novel antithetic variables method is proposed to further improve the accuracy. According to the simulation results on a 64-tap FIR filter, the ASA and AV methods gain 17 dB and 6 dB on the signal-to-noise ratio (SNR), respectively. The hardware implementation results are also presented in this paper, which illustrates that the proposed ASA-AV-SFIR filter increases 4.6 times hardware efficiency with respect to the existing SFIR schemes.

Recent trends in mobile computing and multimedia application demand low power digital signal processing systems (DSP). The most important block in any DSP system is a finite impulse response (FIR) filter. Here a reliable low power FIR filter is designed using Vedic multipliers which specifically perform addition and shifting operation. The addition is done using full adder with 9 transistors which use only 3 transistor XOR gate. A four tap FIR filter was implemented in microwind 2 electronic design automation tool using CMOS 90nm technology. In the proposed design the power consumption is reduced by 23% and delay has been reduced by 44% when compared with the existing FIR filters.

In recent years, several approaches have been investigated to obtain multiplier-free realizations of digital filters. One approach makes use of periodically time-varying (PTV) structures. The idea is to distribute the computation in time and in space. Distribution in time provides reuse of the same hardware by means of PTV coefficients. Distribution in space increases the number of coefficients but simplifies the values of the coefficients. Computation distribution is based on radix-r number representation, and it can be carried out to the extent that each computation involves a simple coefficient that can be realized using only addition and shift (no hardware multiplier). Previous PTV realizations could not exploit the coefficient symmetry of finite impulse response (FIR) filters to reduce the number of coefficients. This paper proposes design and realizations of FIR filters with punctured radix-8 coefficients belonging to the septuple set {0, ±1, ±2, ±4), which can be implemented using only a shift operation without requiring any hardware multiplier. The realizations exploit the coefficient symmetry to reduce the hardware by about one-half. Due to a non-uniform grid of representation, we apply a modified Karmarkar's linear programming algorithm to find the optimum set of discrete coefficients that minimizes the weighted peak ripple error. Comparison with a conventional FIR filter with sum-of-powers-of-two (SOPOT) coefficients shows that the proposed filter is faster and uses less hardware than one with SOPOT coefficients. However, the punctured radix-8 system has a limit on the achievable ripple.

Finite impulse response (FIR) filters are commonly used in many signal processing systems. In some cases, such as space systems, FIR filters are exposed to radiation sources that cause errors. A number of techniques can be used to protect against those errors. One of them is the use of an arithmetic residue replica of the FIR filter. This replica has a lower cost than the original filter and therefore reduces the overhead compared with replicating the filter. However, some errors may not be detected by the arithmetic residue replica. In this brief, schemes that avoid undetected errors are presented. The proposed techniques are implemented and evaluated showing that they can detect all single errors affecting register bits. The results also show that their implementation requires only a small overhead in circuit complexity for the existing residue-based fault-tolerant FIR filters.

This paper proposes a learning-based superresolution algorithm using text characteristics for text images. The proposed algorithm consists of a learning stage and an inference stage. In the learning stage, a sufficient number of low-resolution (LR) to high-resolution (HR) block pairs are first extracted from various LR–HR image pairs that are composed of texts. Then, we classify those block pairs into 512 clusters and, for each cluster, calculate the optimal two-dimensional (2-D) finite impulse response (FIR) filter to synthesize a high-quality HR block from an LR block and store the block-adaptive 2-D FIR filters in a dictionary with their associated index. In the inference stage, we find the best-matched candidate to each input LR block from the dictionary and synthesize the HR block using the optimal 2-D FIR filter. Finally, an HR image is produced via proper postprocessing. Experimental results show that the proposed algorithm provides superior visual quality to images from previous works and outperforms previous processes in terms of computational complexity.

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