scholarly journals An efficient architecture of iterative logarithm multiplier

2018 ◽  
Vol 7 (2.16) ◽  
pp. 24 ◽  
Author(s):  
Durgesh Nandan ◽  
Jitendra Kanungo ◽  
Anurag Mahajan

Multiplication is one of important arithmetic component for digital signal processing, neural network and image processing. But, it is well known fact that multiplier has most hardware consuming component out of all arithmetic components. Here, it is given a possible solution by using an efficient VLSI architecture of Mitchell’s algorithm based Iterative Logarithmic Multiplier (ILM) with modified architecture of Leading One Detector (LOD) and seamless pipelined technique. The proposed work is based on the hardware minimization at the same error cost than of previously reported architectures. We use VHDL to design the existing and proposed Mitchell’s algorithm based iterative logarithmic multiplier. Both multipliers design are evaluated with the Synopsys design compiler by using 90 nm CMOS technology and compared the results in terms of Data Arrival Time (DAT), area, power, Area Delay Product (ADP) and energy. The proposed Mitchell's based ILM gives 33.18 %, 39.03 % and 31.62 % less ADP, 25.08 %, 38.08 % and 46.72 % less energy for 8, 16, and 32 bits architecture respectively in comparison of the reported ILM. The importance of LODs and seamless pipeline has been shown in an efficient architecture of Mitchell's based ILM. 

2012 ◽  
Vol 241-244 ◽  
pp. 1751-1755
Author(s):  
Yin Bing Zhu ◽  
Ke Jing Cao ◽  
Bao Li

Auto-search is one of the key steps in digital signal processing for Loran-C receivers, however, for digital sampling Loran-C signal, the principle search algorithm is unable to realize signal search veraciously because of the asynchronism between sampling clock and transmitting station clock. For this question, an auto-search algorithm based on subsection correlation for Loran-C is presented after analyzing the principle search algorithm. The experiment results show that for the received digital Loran-C signal, there are several correlation and accumulation values of master and secondary stations to exceed the search thresholds; the maximum correlation and accumulation value of the presented algorithm is far higher than that of the principle algorithm. That is to say, the presented algorithm can search the arrival time of master and secondary station successfully, solve the problem of clock asynchronism effectively, and enhance the search sensitivity of the receiver, which have great significance for digital processing of Loran-C signal and the engineering realization of Loran-C digital receiver.


2020 ◽  
Vol 29 (14) ◽  
pp. 2050233
Author(s):  
Zhixi Yang ◽  
Xianbin Li ◽  
Jun Yang

As many digital signal processing (DSP) applications such as digital filtering are inherently error-tolerant, approximate computing has attracted significant attention. A multiplier is the fundamental component for DSP applications and takes up the most part of the resource utilization, namely power and area. A multiplier consists of partial product arrays (PPAs) and compressors are often used to reduce partial products (PPs) to generate the final product. Approximate computing has been studied as an innovative paradigm for reducing resource utilization for the DSP systems. In this paper, a 4:2 approximate compressor-based multiplier is studied. Approximate 4:2 compressors are designed with a practical design criterion, and an approximate multiplier that uses both truncation and the proposed compressors for PP reduction is subsequently designed. Different levels of truncation and approximate compression combination are studied for accuracy and electrical performance. A practical selection algorithm is then leveraged to identify the optimal combinations for multiplier designs with better performance in terms of both accuracy and electrical performance measurements. Two real case studies are performed, i.e., image processing and a finite impulse response (FIR) filter. The design proposed in this paper has achieved up to 16.96% and 20.81% savings on power and area with an average signal-to-noise ratio (SNR) larger than 25[Formula: see text]dB for image processing; similarly, with a decrease of 0.3[Formula: see text]dB in the output SNR, 12.22% and 30.05% savings on power and area have been achieved for an FIR filter compared to conventional multiplier designs.


2020 ◽  
Vol 20 (1) ◽  
pp. 24-34
Author(s):  
A. N. Ragozin ◽  

n order to detect anomalies and improve the quality of forecasting dynamic data flows observed from sensors in Industrial Control System (ACS)., it is proposed to use a predictive mod-ule consisting of a series-connected digital signal processing unit (DSP) and a predictive unit using a neural network (predictive autoencoder ( Auto Encoder), predictive Autoencoder (PAE)). The study showed that the preliminary DSP block of the predicted input signal, consisting of a parallel set (comb) of digital low-pass filters with finite impulse responses (FIR-LPF), leads to a non-equilibrium account of the correlation relationships of the time samples of the input signal and to increase the accuracy of the final prediction result. The predicted autoencoder (PAE) pro-posed and considered in the work, in addition to restoring the input signal or part of the input signal at the PAE output, also generates the predicted samples of the input signal for the speci-fied number of «forward» time steps at the output, which increases the accuracy of the predic-tion result. The reduction of the forecast error occurs due to the imposition of restrictions in the formation of the forecast, that is, an additional requirement to restore the input samples of the samples – «stabilizers» at the NS output. The introduction of «stabilizers» increases the accuracy of the prediction result.


2013 ◽  
Vol 107 (1) ◽  
pp. 46-53 ◽  
Author(s):  
Jason Silverman ◽  
Gail L. Rosen ◽  
Steve Essinger

Use digital signal processing to capitalize on an exciting intersection of mathematics and popular culture.


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