power. However, this method used the built-in block multipliers of Virtex II field-programmable gate array (FPGA) and there was no consideration for the complexity **reduction** of the **FIR** **filter**. The concept of reconfigurable multiplier block (ReMB) was introduced. The ReMB will generate all the coefficient products and a multiplexer will select the required ones depending on the input. It was shown that by pushing the multiplexer deep into the multiplier block design, the redundancy can be reduced. The resulting specialized multiplier design can be more efficient in terms of area and computational complexity compared to the general- purpose multiplier plus the coefficient store. But the ReMB proposed in has its area, power, and speed dependent on the **filter**-length making them inappropriate for higher **order** **FIR** filters. In multiplexed multiple constant multiplications (MMCM) approach was proposed. This method considers the coefficient set as a constant and uses the graph dependence (GD) algorithms for reducing redundancy. But this method follows a directed acyclic graph structure which will result in long LD and thus lower speed of operation as reported in [3], [4]. Also the area of the architecture linearly increases with the **filter** length as in filters with **filter**-length above 40 are infeasible. In the common digital signal processing (DSP) operations such as filtering and matrix multiplication were identified and expressed as vector scaling operations. In **order** to apply vector scaling, simple number decomposition strategies were identified. The idea was to precompute the values such as x, 3x, 5x, 7x, 9x, 11x, 13x, and 15x, where x is the input signal and then reuse these precomputations efficiently using multiplexers. The presence of multiplexers gave the option of adaptive computing for the method in. In the method was modified and efficient circuit-level techniques, namely a new carry select adder and conditional capture flip-flop, were used to further improve power and performance. The architectures are appropriate only for relatively lower **order** filters and hence not suitable for channel filters in communication receivers. Although a few works addressed the problem of reducing the complexity of coefficient multipliers in reconfigurable **FIR** filters, hardly any work demonstrated reconfigurability in higher **order** filters. Moreover, we note that there is sufficient scope for more work on complexity **reduction** in reconfigurable filters especially for wireless communication applications where higher **order** filters are often required to meet the stringent adjacent channel attenuation specifications.

Show more
able to achieve an area efficiency of 62% and maximum path delay efficiency of 77% in comparison to [28]. This proposed multiplier is then used in **FIR** filters and the complexity **reduction** in **filter** is verified. The maximum frequency of operation of the **filter** achieved is also higher in proposed multiplier design-based **filter**. The hardware utilised, as external control circuit for an N-th **order** **filter** by our proposed design are, N(2([W+8]/2))-bit adders, N(2(2 to 1)) mux. The hardware utilised by the OMS design [28] are N(2(4 to 3)) encoder, N(2(W+4))-bit NOR gates, N(2(W+4)-bit AOI gates, N(2(2-bit)) NOR gates, N(2(2-bit)) OR gates apart from dual core memory, decoder and shift adder which is used by both the designs. For a 32-**order** **filter**, filtering an input with a word length of 8, the area efficiency achieved using our multiplier is 26%. For any DSP application we require higher **order** **filter** and for better performance the word length of the input should be high. For higher **order** filtering with larger input length, our proposed **filter** is a better alternative compared to other optimised design proposed till now under memory-based filters.

Show more
15 Read more

The objective of the paper is to reduce the hardware complexity of higher **order** **FIR** **filter** with symmetric coefficients. The aim is to design efficient Fast Finite-Impulse Response (**FIR**) Algorithms (FFAs) for parallel **FIR** **filter** structure with the constraint that the **filter** tap must be a multiple of 2. In our work we have briefly discussed for L = 4 parallel implementation. The parallel **FIR** **filter** structure based on proposed FFA technique has been implemented based on carry save and ripple carry adder for further optimization. The **reduction** in silicon area complexity is achieved by eliminating the bulky multiplier with an adder namely ripple carry and carry save adder. For example, for a 6-parallel 1024-tap **filter**, the proposed structure saves 14 multipliers at the expense of 10 adders, whereas for a six-parallel 512-tap **filter**, the proposed structure saves 108 multipliers at the expense of 10 adders. Overall, the proposed parallel **FIR** structures can lead to significant hardware savings for symmetric coefficients from the existing FFA parallel **FIR** **filter**, especially when the length of the **filter** is very large.

Show more
DA is a bit-serial operation that implements a series of fixed-point MAC operations in a fixed number of steps, regardless of the number of terms to be calculated. One problem with original DA architecture is that its LUT size (2K-words) grows exponentially as the **filter** **order** N increase. If the inner-products are implemented in a straight-forward way, the memory-size of DA based implementation increases exponentially with the inner-product-length. Attempts have been made to reduce the memory-space in DA-based architectures for reducing the memory-size of DA-based implementation of **FIR** **filter**. But, it is observed that the **reduction** of memory-size achieved by such decomposition is accompanied by increase in latency as well as the number of adders and latches.

Show more
most widely used fundamental devices performed in DSP systems, ranging from wireless communications to video and image processing. Some applications need the **FIR** **filter** to operate at high frequencies such as video processing, whereas some other applications request high throughput with a low-power circuit such as multiple-input– multiple-output systems used in cellular wireless communication. Furthermore, when narrow transition band characteristics are required, the much higher **order** in the **FIR** **filter** is unavoidable. In this brief, parallel processing in the digital **FIR** **filter** will be discussed. Due to its linear increase in the hardware implementation cost brought by the increase in the block size L, the parallel processing technique loses its advantage to be employed in practice.

Show more
In [11], the **filter** design objective was modified to the Normalized Peak Ripple Mag- nitude. This was owed to the fact that a filter’s purpose is to alter an incoming signal to allow one set of frequencies while attenuating another set of frequencies. Thus, a gain of unity was inconsequential. However, a constraint had to be set on the passband gain. A high gain meant a better signal to noise ratio but it also caused overflow. In the discrete power of two space, the upper bound and lower bound of the passband gain differed by two i.e. the lower bound was always half the upper bound. This was because any other gain could always be represented in the given range by multiplying or diving by a suitable power of two and the NPRM would remain the same. To find a coefficient set with the op- timal NPRM, passband gain sectioning was introduced. In the gain sectioning technique, the gain range was divided into many fine gain sections and a discrete **filter** was designed using the upper bound and lower bound constraints of the section on the gain. A simple technique was to section the range [0.7, 1.4] and select the best solution found among all the sections. A trade off was met between design quality and design time as more sections led to a better design but with increased design time. A more involved technique based on elimination was also given.

Show more
120 Read more

Abstract The need of effective method to obtain and analyse electrocardiogram (EKG) signal has inspired This research paper to designed an efficient algorithm that can handle any (EKG), remove the most dominant noises associated with it, and extract the important futures. EKG signal is an electrical signal represents the physical human’s heart activity. Nonetheless, this signal is affected by various noise including baseline wondering and power interference. These noises affect the signal to noise ratio (SNR) especially in P and T waves which have less amplitudes than R peaks. Removing these noises result in cleaner signal that can be conveniently processed to extract important features such as heart health condition. EKG features play the main role in diagnosing the heart rate, normality and abnormality of heart activities, and heart diseases. For a healthy person, one heart beat consists of P, QRS Complex, T, and in some signals U waves. In this paper, a robust and numerically sufficient algorithm is developed to de-nosing EKG signal and extract all major features. For de-nosing EKG signal, **FIR** Equiripple High pass **filter** is used. **FIR** Equiripple Low pass **filter** follows this **filter** to remove the power interference noises. Haar wavelet transform is used to accurately detect the R peaks. Haar wavelet is found to be better than other common methods that are used to detect R peaks. Haar wavelet shows high accuracy when it is applied on EKG signal to detect R peaks. In fact, it succeeded to detect all R peaks in hundreds of EKG signals (obtained from Physio net website). All other features are detected based on the R peaks by creating a set of windows which their lengths depend on the maximum normal wave durations and locations. These filters and algorithm have been implemented in Matlab. The algorithm has been applied on 108 EKG signals collected from physionet website and could detect all EKG signals’ heart rates successfully despite the fact that some signals were extremely distorted.

Show more
22 Read more

Fig 7 RTL schematic for a Wallace tree and Kogge stone adder The RTL schematic and the LUT schematics are generated using the codes written in the ISE design suite using Verilog coding. We have also generated a basic structure of **FIR** **filter** using the MATLAB Simulink and Xilinx ISE design suite by using the System generator. We have dumped the Verilog code for the Wallace tree and the kogge stone adders individually into the black box elements of the Simulink. We have seen the outputs and verified it‟s working.

Modified Carry-Save Adder consumes more delay and area due to propagation delay and sequential process [5]. Hence Improved Carry-Save Adder (ICSA) is designed in this work with parallel processing and without carry propagation delay. Our ICSA adder offers less area and higher speed than all other schemes. Regular Wal- lace and reduced Wallace Multipliers are designed using different high speed adders [6]. But it consumes more area, power and less delay [7]-[9]. So compact full adder, half adder and ICSA adder are incorporated into Wal- lace to improve the efficiency of our multiplier. Several previous endeavors for reducing area, delay and power consumption of digital **FIR** **filter** usually focus on the optimization of the **filter** coefficient while the **filter** **order** is fixed [10]. **FIR** **filter** structures are simplified to, minimizing the number of additions/subtractions & Add and Shift operations which is the main focus of those approaches. However, one of the drawbacks encountered in those approaches is that once the **filter** architecture is determined, the coefficients cannot be altered [11]. Con- sequently, those schemes are not appropriate to the **FIR** **filter** with programmable coefficients [12]. Reconfigur- able **FIR** **filter** with modified Amplitude Detector (AD) and control logic is introduced to reduce the area and power utilization [13]. But it makes performance degradation. Previously described works have been focused on reducing the power consumption and improving the configuration of **filter** coefficients. However, all those ar- chitectures have more complexity, because of using traditional hardware structures to perform multiplication and accumulation functions. In **order** to reduce the hardware complexity of MAC unit, redundant logical func- tions are identified with the help of Boolean expressions. It is identified that half adder and full adder are used in every digital signal processing operation like MAC and ALU. Hence, the redundant Boolean logical expressions of half adder and full adder are identified to optimize the digital signal processing operations. So our proposed Direct **FIR** **filter** offers optimum area, delay and power compared with the all other **filter** techniques also without any degradation. Because Enhanced Wallace Multiplier with Improved Carry-Save adder is incorporated into proposed **FIR** **filter**.

Show more
Accordingly, this paper proposes two methods for opti- mising the numerical computation of di/dt of fault current transients and evaluates the quality of the derived ROCOC measurement for each using a simulated model of a DC microgrid with artificially injected measurement noise. The first method is an approach to derive the optimised selection of sampling frequency for a current measurement signal whilst minimising noise pickup. The second method is the application of a tuned finite impulse response (**FIR**) **filter** to condition the signal prior to discrete di/dt computation. Practical application of these signal conditioning methods are then discussed for di/dt-based fault detection algorithms for future high-speed DC protection devices.

Show more
The main contribution of the work done here is the implementation of HS Algorithm and adapting the algorithm to utilise it in designing **FIR** filters and neural networks. The algorithm has been initially used for several other applications mentioned in Chapter 2. The disadvantage of the other algorithms like GA and PSO is that they require fine tuning of parameters in **order** to obtain a feasible solution. Also, diversification and intensification are the two major components whose balanced combination is very important for the success of any metaheuristic algorithm. Harmony search successfully balances these two major components by pitch adjustment and harmony considering rate and therefore it ensures a certain level of efficiency and that the evolving system will not get trapped in the local minima.

Show more
84 Read more

We research ship 6 DOF inertial measurement method and displacement reconstruction form ac- celeration signal to establish the strap-down inertial navigation measurement system through sensors configuration technology. The inertial measurement system consists of three groups of vertically mounted angular rate and acceleration sensors. Through designing an **FIR** integration **filter** and studying the ship displacement signal reconstruction from the acceleration, the **filter** parameters design method and implementation way were determined. By means of the beam vi- bration to analog ship heave motion reconstructs linear displacement form acceleration signals. The root mean square error of the reconstructed line displacement is 0.004 mm, and the mean value of the displacement peak value is 5.92%, which is close to the design precision of the **filter**. The test shows that the measurement system and the **FIR** **filter** to achieve the predetermined pre- cision with noise suppression.

Show more
10 Read more

Abstract: Digital filters has developed a lot of applications on different fields. Fundamentally, Filters are used to remove the unwanted frequencies from applied signal which have both wanted and unwanted signals. Digital filters are of two types: Infinite impulse response (IIR) and finite impulse response (**FIR**). Infinite impulse response digital filters are recursive (feedback type) systems that involve fewer design parameters, less memory requirements, and lower computational complexity than finite impulse response digital filters. This paper represents the comparison of both IIR and **FIR** filters to find the better most technique for digital signal. importance.

Show more
Signal Processing Toolbox™ provides functions and apps to generate, measure, transform, **filter**, and visualize signals. The toolbox includes algorithms for resampling, smoothing, and synchronizing signals, designing and analyzing filters, estimating power spectra, and measuring peaks, bandwidth, and distortion. One can use Signal Processing Toolbox to analyze and compare signals in time, frequency, and time-frequency domains, identify patterns and trends, extract features, and develop and validate custom algorithms to gain insight into your data.

Show more
13 Read more

The fields like mobile communication and DSP increased quick growth to form complex frameworks into a solitary chip for example system on-Chip (SoC). It is discovered that this single chip framework has great execution, diminished size, and less power utilization than ordinary plan procedure [1]. Here finite impulse response is used for faster operations. Basically, finite impulse response is nothing but a **filter** where the impulse response remains fine duration. In signal processing, a finite impulse response (**FIR**) is used. In the same way it settles zero at finite time. This **FIR** **filter** is mainly used in digital signal processing applications. Basically, **FIR** **filter** is a signal conditioner; it allows the AC components and blocks the DC components. The example of **FIR** **filter** is phone line. In the **FIR** **filter** all signal frequencies are delayed in the same amount of time. For finite input it all the signals in **filter** remains stable.

Show more
Microprocessors use a clock to execute different programmed steps in a sequential manner, it is possible that an error in reading memory can cause the processor to hang. For critical real time measurements, such as a PMU, this is normally overcome by including a dead-man timer, to reboot the processor if this were to occur. In FPGAs, semi-permanent programmable connections are made in the digital logic hardware. The hardware is event driven, a change in input causes an immediate change in the output. All the required functions are operated in parallel. Clocks can be used to perform some sequential events or to synchronize and buffer data as needed. Modern FPGAs are instantly ON and do not require any programming at startup. Not requiring a dead-man timer, ensures that an FPGA implementation of a PMU has a better reliability than a PMU implemented with microprocessors. The proposed FPGAs includes sufficient hardware multipliers for all the IIR **filter** stages, so that the digital signal processing (DSP) calculations shown in Figure 2 can be completed in much less than the 0.1 ms sampling period. In comparison, it takes 0.5 ms to perform the multiplications for one new input to an IEC/IEEE Std **FIR** reference **filter** with 400 taps using an Intel i7-9700 based PC. The PMUs latency includes both the DSP calculation time and the group delay of the filters used in a PMU algorithm. Minimizing the calculation time allows for a higher group delay of the filters and thus a higher attenuation for out-of-band signals and harmonics.

Show more
18 Read more

Digit serial **FIR** **Filter** for low power can be designed using 1.Digit Serial Adder Figure shows the Digit-serial architecture for word length of 4 (W=4). This adder adds two four digit numbers x3x2x1x0 and y3y2y1y0 to get 4 digit sum s3s2s1s0 where bit 0 is the least significant bit and bit 3 is the most significant bit. Initially cin=0, we have to kept cin=0 using switch, after it we force full-adder with data x0y0 we get the value of sum s0. For next iteration we connect cout to cin using switch and we force the full-adder x1y1 we get the value of s1 and so on.

Show more
ABSTRACT: This paper deals the designing as well as application of the constrained least squares multiband **FIR** digital **filter** on the electromagnetic Schumann resonance (SR) signal, and design methods based on MATLAB simulation. FDATool in MATLAB is used to determine low **order** **filter** coefficients and simulate **FIR** multiband pass filters to find necessary first four modes of SR signal, 8, 14, 20 and 26 Hertz, with the daily variation of about +/- 0.5 Hertz, by employing a set of 3-component search coil magnetometer at tropical station Agra, India (Geograph.lat.27.21N, long. 781E). I also use IIR notch **filter** to remove a big sharp peak noise due to local interference (like train noise) in the SR signal. The results prove that the performance of the designed low **order** multiband **FIR** **filter** reaches the appointed requirement. The result shows before filtering and after filtering the SR signal, which clearly indicates the measurement of continuous SR signal frequencies and corresponding intensities are accurate for each channel.

Show more
219 with transposed structure has registers between the adders and can achieve high throughput without adding any extra pine line registers. Transposed form is self pipelined with the cycle period the delay of an adder and a multiplier. But it has more area than directed form. You can add delay even in directed form or transposed form to make the design faster which resulted in mixed form. Here figure ‘a’ shows the area which is consumed by **filter** called combinational and non-combinational area. Here combinational area is greater than the non-combinational area. Figure ‘b’ shows the internal power required for the execution.

Show more
10 Read more