Journal articles: 'Log-domain filter'

1

Georgiou, P., and C. Toumazou. "Chemical log-domain filter." Electronics Letters 45, no. 8 (2009): 391. http://dx.doi.org/10.1049/el.2009.0152.

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Kasimis, Chrisostomos, George Souliotis, and Costas Psychalinos. "Novel log-domain frequency-adaptive filter." International Journal of Electronics 99, no. 2 (February 2012): 197–209. http://dx.doi.org/10.1080/00207217.2011.623273.

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3

FRAGOULIS, NIKOS, GEORGE SOULIOTIS, and KONSTANTINE GIANNAKOPOULOS. "A LOG-DOMAIN WAVE POSITIVE IMPEDANCE INVERTER." Journal of Circuits, Systems and Computers 17, no. 04 (August 2008): 561–67. http://dx.doi.org/10.1142/s0218126608004502.

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A new log-domain building block for log-domain filter design is proposed in this paper. This block realizes a positive impedance inverter (gyrator) by using the log-domain wave method. A simple procedure for log-domain filter development, using the proposed block, is outlined. This method results in circuits, which are simple in structure and very easy to design. An example of a second-order bandpass filter is given and its functionality is verified through simulations.

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4

WU, JIE, and EZZ I. EL-MASRY. "Log-domain synthesis of annth-order filter." International Journal of Electronics 84, no. 4 (April 1998): 359–69. http://dx.doi.org/10.1080/002072198134715.

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5

Frey, D. R., and E. M. Drakakis. "Unifying perspective on log-domain filter synthesis." Electronics Letters 45, no. 17 (2009): 861. http://dx.doi.org/10.1049/el.2009.1960.

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6

Toumazou, C., J. Ngarmnil, and T. S. Lande. "Micropower log-domain filter for electronic cochlea." Electronics Letters 30, no. 22 (October 27, 1994): 1839–41. http://dx.doi.org/10.1049/el:19941284.

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7

Liu, Shen-Iuan, and Yu-Hung Liao. "Table-based log-domain linear transformation filter." Electronics Letters 32, no. 19 (1996): 1771. http://dx.doi.org/10.1049/el:19961181.

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8

Mahattanakul, J., and C. Toumazou. "Modular log-domain filters based upon linear Gm-C filter synthesis." IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications 46, no. 12 (1999): 1421–30. http://dx.doi.org/10.1109/81.809544.

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9

Kircay, Ali, and Ugur Cam. "A Novel Log-Domain First-Order Multifunction Filter." ETRI Journal 28, no. 3 (June 9, 2006): 401–4. http://dx.doi.org/10.4218/etrij.06.0205.0117.

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Shah, Nisar Ahmad, and Farooq Ahmad Khanday. "Log-domain synthesis of nth order universal filter." Analog Integrated Circuits and Signal Processing 59, no. 3 (December 9, 2008): 309–15. http://dx.doi.org/10.1007/s10470-008-9258-6.

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11

Shah, N. A., S. Z. Iqbal, and Nusrat Parveen. "Log-domain all pass filter based on integrators." Analog Integrated Circuits and Signal Processing 67, no. 1 (December 30, 2010): 85–88. http://dx.doi.org/10.1007/s10470-010-9584-3.

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12

Punzenberger, M., and C. C. Enz. "A compact low-power BiCMOS log-domain filter." IEEE Journal of Solid-State Circuits 33, no. 7 (July 1998): 1123–29. http://dx.doi.org/10.1109/4.701278.

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13

Frey, D. R., and Y. P. Tsividis. "Syllabically companding log domain filter using dynamic biasing." Electronics Letters 33, no. 18 (1997): 1506. http://dx.doi.org/10.1049/el:19971043.

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14

Kircay, Ali, and Ugur Cam. "A novel first-order log-domain allpass filter." AEU - International Journal of Electronics and Communications 60, no. 6 (June 2006): 471–74. http://dx.doi.org/10.1016/j.aeue.2005.06.003.

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15

Gentner, Christian, Siwei Zhang, and Thomas Jost. "Log-PF: Particle Filtering in Logarithm Domain." Journal of Electrical and Computer Engineering 2018 (2018): 1–11. http://dx.doi.org/10.1155/2018/5763461.

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This paper presents a particle filter, called Log-PF, based on particle weights represented on a logarithmic scale. In practical systems, particle weights may approach numbers close to zero which can cause numerical problems. Therefore, calculations using particle weights and probability densities in the logarithmic domain provide more accurate results. Additionally, calculations in logarithmic domain improve the computational efficiency for distributions containing exponentials or products of functions. To provide efficient calculations, the Log-PF exploits the Jacobian logarithm that is used to compute sums of exponentials. We introduce the weight calculation, weight normalization, resampling, and point estimations in logarithmic domain. For point estimations, we derive the calculation of the minimum mean square error (MMSE) and maximum a posteriori (MAP) estimate. In particular, in situations where sensors are very accurate the Log-PF achieves a substantial performance gain. We show the performance of the derived Log-PF by three simulations, where the Log-PF is more robust than its standard particle filter counterpart. Particularly, we show the benefits of computing all steps in logarithmic domain by an example based on Rao-Blackwellization.

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16

Fox, R. M., and M. Nagarajan. "Multiple operating points in a CMOS log-domain filter." IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing 46, no. 6 (June 1999): 705–10. http://dx.doi.org/10.1109/82.769779.

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17

Ferrer, E., and R. M. Fox. "Limit-cycle oscillations in a log-domain-based filter." IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing 46, no. 6 (June 1999): 832–36. http://dx.doi.org/10.1109/82.769794.

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18

Ma, Sheng Qian, Li Rong Zheng, Yong Jie Ma, Wei Zhao Zhang, and Zhi Feng Ma. "Design of the adaptive log-domain low-pass filter." MATEC Web of Conferences 44 (2016): 01034. http://dx.doi.org/10.1051/matecconf/20164401034.

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19

Sabir, Dilshad, Muhammmad Abdullah Hanif, Ali Hassan, Saad Rehman, and Muhammad Shafique. "Weight Quantization Retraining for Sparse and Compressed Spatial Domain Correlation Filters." Electronics 10, no. 3 (February 2, 2021): 351. http://dx.doi.org/10.3390/electronics10030351.

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Using Spatial Domain Correlation Pattern Recognition (CPR) in Internet-of-Things (IoT)-based applications often faces constraints, like inadequate computational resources and limited memory. To reduce the computation workload of inference due to large spatial-domain CPR filters and convert filter weights into hardware-friendly data-types, this paper introduces the power-of-two (Po2) and dynamic-fixed-point (DFP) quantization techniques for weight compression and the sparsity induction in filters. Weight quantization re-training (WQR), the log-polar, and the inverse log-polar geometric transformations are introduced to reduce quantization error. WQR is a method of retraining the CPR filter, which is presented to recover the accuracy loss. It forces the given quantization scheme by adding the quantization error in the training sample and then re-quantizes the filter to the desired quantization levels which reduce quantization noise. Further, Particle Swarm Optimization (PSO) is used to fine-tune parameters during WQR. Both geometric transforms are applied as pre-processing steps. The Po2 quantization scheme showed better performance close to the performance of full precision, while the DFP quantization showed further closeness to the Receiver Operator Characteristic of full precision for the same bit-length. Overall, spatial-trained filters showed a better compression ratio for Po2 quantization after retraining of the CPR filter. The direct quantization approach achieved a compression ratio of 8 at 4.37× speedup with no accuracy degradation. In contrast, quantization with a log-polar transform is accomplished at a compression ratio of 4 at 1.12× speedup, but, in this case, 16% accuracy of degradation is noticed. Inverse log-polar transform showed a compression ratio of 16 at 8.90× speedup and 6% accuracy degradation. All the mentioned accuracies are reported for a common database.

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20

Shah, N. A., and F. A. Khanday. "A Generic Current Mode Design for Multifunction Grounded Capacitor Filters Employing Log-Domain Technique." Active and Passive Electronic Components 2011 (2011): 1–10. http://dx.doi.org/10.1155/2011/313580.

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A generic design (GD) for realizing annth order log-domain multifunction filter (MFF), which can yield four possible stable filter configurations, each offering simultaneously lowpass (LP), highpass (HP), and bandpass (BP) frequency responses, is presented. The features of these filters are very simple, consisting of merely a few exponential transconductor cells and capacitors; all grounded elements, capable of absorbing the shunt parasitic capacitances, responses are electronically tuneable, and suitable for monolithic integration. Furthermore, being designed using log-domain technique, it offers all its advantages. As an example, 5th-order MFFs are designed in each case and their performances are evaluated through simulation. Lastly, a comparative study of the MFFs is also carried, which helps in selecting better high-order MFF for a given application.

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21

Kircay, A., and U. Cam. "Differential Type Class-AB Second-Order Log-Domain Notch Filter." IEEE Transactions on Circuits and Systems I: Regular Papers 55, no. 5 (June 2008): 1203–12. http://dx.doi.org/10.1109/tcsi.2008.916458.

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22

López-MartÍn, Antonio J., Rubén Fernández, Carlos A. de la Cruz Blas, and Alfonso Carlosena. "A 1 V Micropower FGMOS Class AB Log-Domain Filter." Analog Integrated Circuits and Signal Processing 41, no. 2/3 (December 2004): 137–45. http://dx.doi.org/10.1023/b:alog.0000041631.38645.c7.

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23

Fares, Osama O. "Log-domain electronically-tuneable fully differential high order multi-function filter." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 2 (April 1, 2020): 1263. http://dx.doi.org/10.11591/ijece.v10i2.pp1263-1272.

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This paper presents the synthesis of fully deferential circuit that is capable of performing simultaneous high-pass, low-pass, and band-pass filtering in the log domain. The circuit utilizes modified Seevinck’s integrators in the current mode. The transfer function describing the filter is first presented in the form of a canonical signal flow graph through applying Mason’s gain formula. The resulting signal flow graph consists of summing points and pick-off points associated with current mode integrators within unity-gain negative feedback loops. The summing points and the pick-off points are then synthesized as simple nodes and current mirrors, respectively. A new fully differential current-mode integrator circuit is proposed to realize the integration operation. The proposed integrator uses grounded capacitors with no resistors and can be adjusted to work as either lossless or lossy integrator via tuneable current sources. The gain and the cutoff frequency of the integrator are adjustable via biasing currents. Detailed design and simulation results of an example of a 5th order filter circuit is presented. The proposed circuit can perform simultaneously 5th order low-pass filtering, 5th order high-pass filtering, and 4th order band-pass filtering. The simulation is performed using Pspice with practical Infineon BFP649 BJT model. Simulation results show good matching with the target.

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24

Punzenberger, M., and C. C. Enz. "A 1.2-V low-power BiCMOS class AB log-domain filter." IEEE Journal of Solid-State Circuits 32, no. 12 (1997): 1968–78. http://dx.doi.org/10.1109/4.643655.

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25

Python, D., and C. C. Enz. "A micropower class-AB CMOS log-domain filter for DECT applications." IEEE Journal of Solid-State Circuits 36, no. 7 (July 2001): 1067–75. http://dx.doi.org/10.1109/4.933462.

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26

Ascoli, Alon, Orla Feely, and Paul Curran. "On the Chaotic Behavior of a Third-Order Log-Domain Filter." Nonlinear Dynamics 44, no. 1-4 (June 2006): 45–54. http://dx.doi.org/10.1007/s11071-006-1934-4.

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27

Gul, Tuba Nur, and Ali Kircay. "The Design of Fifth-Order Butterworth Lowpass Log-Domain Filter for Bluetooth/Wi-Fi Receiver Using Signal Flow Graph Method." Journal of Circuits, Systems and Computers 26, no. 01 (October 4, 2016): 1750011. http://dx.doi.org/10.1142/s0218126617500116.

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In this study, a fifth-order lowpass log-domain Butterworth filter, which is appropriate for Bluetooth/Wi-Fi receiver, is designed with signal flow graph approach. The filter is realized by using a unique translinear integrator circuit. Bluetooth and Wi-Fi modes are obtained without changing the circuit configuration. To change the mode of the filter, it is needed to change the cutoff frequency of the filter that can be electronically tuned by adjusting the external currents. Wi-Fi and Bluetooth receivers have 6[Formula: see text]MHz and 600[Formula: see text]kHz cutoff frequencies, respectively. Only BJTs and grounded capacitors were utilized to achieve the desired circuit. Lowpass log-domain Butterworth filter was simulated by using SPICE simulation program. A validated BJT and idealized BJT models are used to obtain simulation results confirming the theoretical analysis.

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Jain, Manoj Kumar, and Vinod Kumar Singh. "New Log-Domain First-Order Multifunction Filter Using MOSFETs in Weak Inversion." Circuits and Systems 07, no. 11 (2016): 3522–30. http://dx.doi.org/10.4236/cs.2016.711299.

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29

Teplechuk, M. A., and J. I. Sewell. "Approximation of arbitrary complex filter responses and their realisation in log domain." IEE Proceedings - Circuits, Devices and Systems 153, no. 6 (2006): 583. http://dx.doi.org/10.1049/ip-cds:20060021.

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30

Manetti, Stefano, and Maria Cristina Piccirilli. "Log-Domain Filter Design Based on Impedance Scaling of LC Ladder Structures." Circuits, Systems, and Signal Processing 30, no. 2 (November 17, 2010): 371–89. http://dx.doi.org/10.1007/s00034-010-9227-z.

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31

Leung, V. W., and G. W. Roberts. "Effects of transistor nonidealities on high-order log-domain ladder filter frequency responses." IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing 47, no. 5 (May 2000): 373–87. http://dx.doi.org/10.1109/82.842106.

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32

G., Hanumantha Rao, and Rekha S. "An area‐efficient, large time‐constant log‐domain filter for low‐frequency applications." International Journal of Circuit Theory and Applications 48, no. 2 (December 9, 2019): 170–80. http://dx.doi.org/10.1002/cta.2726.

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33

Tola, Abdullah T., Remzi Arslanalp, and Saziye Surav Yilmaz. "Current mode high-frequency KHN filter employing differential class AB log domain integrator." AEU - International Journal of Electronics and Communications 63, no. 7 (July 2009): 600–608. http://dx.doi.org/10.1016/j.aeue.2008.04.015.

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34

Fomel, Sergey. "Seismic reflection data interpolation with differential offset and shot continuation." GEOPHYSICS 68, no. 2 (March 2003): 733–44. http://dx.doi.org/10.1190/1.1567243.

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I propose a finite‐difference offset‐continuation filter for interpolating seismic reflection data. The filter is constructed from the offset‐continuation differential equation and is applied on frequency slices in the log‐stretch frequency domain. Synthetic and real data tests demonstrate that the proposed method succeeds in structurally complex situations where more simplistic approaches fail.

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Ip, Henry Man D., Emmanuel Mic Drakakis, and Anil A. Bharath. "A 19nW analogue CMOS log-domain 6th-order Bessel filter without E-minus cells." Microelectronics Journal 40, no. 8 (August 2009): 1170–74. http://dx.doi.org/10.1016/j.mejo.2009.01.008.

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36

Wang, Zheng. "Analysis of DNS Cache Effects on Query Distribution." Scientific World Journal 2013 (2013): 1–8. http://dx.doi.org/10.1155/2013/938418.

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This paper studies the DNS cache effects that occur on query distribution at the CN top-level domain (TLD) server. We first filter out the malformed DNS queries to purify the log data pollution according to six categories. A model for DNS resolution, more specifically DNS caching, is presented. We demonstrate the presence and magnitude of DNS cache effects and the cache sharing effects on the request distribution through analytic model and simulation. CN TLD log data results are provided and analyzed based on the cache model. The approximate TTL distribution for domain name is inferred quantificationally.

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37

Drakakis, E. M., and A. J. Burdett. "Operational dc constraints for a class-a, third-order, observer canonical-form log-domain filter." IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications 50, no. 10 (October 2003): 1337–42. http://dx.doi.org/10.1109/tcsi.2003.816328.

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Victoria.L, Baby, and Sathappan S. "A sporadic decomposition of Hankel structured matrix in logarithmic and wavelet domain for impulse noise removal." International Journal of Engineering & Technology 7, no. 4 (September 17, 2018): 2309. http://dx.doi.org/10.14419/ijet.v7i4.16694.

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Noise removal from the color images is the most significant and challenging task in image processing. Among different conventional filter methods, a robust Annihilating filter-based Low-rank Hankel matrix (r-ALOHA) approach was proposed as an impulse noise removal algorithm that uses the sparse and low-rank decomposition of a Hankel structured matrix to decompose the sparse impulse noise components from an original image. However, in this algorithm, the patch image was considered as it was sparse in the Fourier domain only. It requires an analysis of noise removal performance by considering the other transform domains. Hence in this article, the r-ALOHA can be extended into other transform domains such as log and exponential. In the log and exponential domain, the logarithmic and exponential functions are used for modeling the multiplicative noise model. But, this model is used only for positive outcomes. Therefore, wavelet transform domain is applied to the noise model that localizes an image pixel in both frequency and time domain simultaneously. Moreover, it separates the most vital information in a given image. Thus, it is feasible for obtaining a better approximation of the considered function using few coefficients. Finally, the experimental results show the performance effectiveness of the proposed algorithm.

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39

Gerosa, A., A. Maniero, and A. Neviani. "A Fully Integrated Dual-Channel Log-Domain Programmable Preamplifier and Filter for an Implantable Cardiac Pacemaker." IEEE Transactions on Circuits and Systems I: Regular Papers 51, no. 10 (October 2004): 1916–25. http://dx.doi.org/10.1109/tcsi.2004.835027.

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40

kircay, Ali, and Ugur Cam. "A new 5th-order differential type class-AB log-domain elliptic lowpass filter for video frequency applications." Analog Integrated Circuits and Signal Processing 60, no. 3 (March 10, 2009): 221–29. http://dx.doi.org/10.1007/s10470-009-9292-z.

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41

Wang, K., T. Yu, Q. Y. Meng, G. K. Wang, S. P. Li, and S. H. Liu. "Edge Detection from High Resolution Remote Sensing Images using Two-Dimensional log Gabor Filter in Frequency Domain." IOP Conference Series: Earth and Environmental Science 17 (March 18, 2014): 012191. http://dx.doi.org/10.1088/1755-1315/17/1/012191.

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42

Garreton, Claudio, and Nestor Becerra Yoma. "Telephone Channel Compensation in Speaker Verification Using a Polynomial Approximation in the Log-Filter-Bank Energy Domain." IEEE Transactions on Audio, Speech, and Language Processing 20, no. 1 (January 2012): 336–41. http://dx.doi.org/10.1109/tasl.2011.2157495.

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43

AKITA, I., K. WADA, and Y. TADOKORO. "A 0.8-V Syllabic-Companding Log Domain Filter with 78-dB Dynamic Range in 0.35- m CMOS." IEICE Transactions on Electronics E91-C, no. 1 (January 1, 2008): 87–95. http://dx.doi.org/10.1093/ietele/e91-c.1.87.

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44

Li, Shutao, Yaonan Wang, and Jie Wu. "Design of low-voltage and low-power fully integrated filter based on log-domain current-mode integrator." Journal of Electronics (China) 18, no. 4 (October 2001): 346–50. http://dx.doi.org/10.1007/s11767-001-0049-9.

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45

Brahara, Beni, Dedy Syamsuar, and Yesi Novaria Kunang. "Analysis of Malware Dns Attack on the Network Using Domain Name System Indicators." Journal of Information Systems and Informatics 2, no. 1 (March 11, 2020): 131–53. http://dx.doi.org/10.33557/journalisi.v2i1.30.

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University of Bina Darma Palembang has its own DNS server and in this study using log data from the Bina Darma University DNS server as data in the study, DNS log server data is analyzed by network traffic, using Network Analyzer tools to see the activity of a normal traffic or anomaly traffic, or even contains DGA Malware (Generating Algorthm Domain).DGA malware produces a number of random domain names that are used to infiltrate DNS servers. To detect DGA using DNS traffic, NXDomain. The result is that each domain name in a group domain is generated by one domain that is often used at short times and simultaneously has a similar life time and query style. Next look for this pattern in NXDomain DNS traffic to filter domains generated algorithmically that the domain contains DGA. In analyzing DNS traffic whether it contains Malware and whether network traffic is normal or anomaly, in this study it detects Malwere DNS From the results of the stages of the suspected domain indicated by malware, a suspected domain list table is also created and also a suspected list of IP addresses. To support the suspected domain analysis results, info graphic is displayed using rappidminer tools to test decisions that have been made using the previous tools using the Decision Tree method.

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46

Bickel, Samuel H. "Similarity and the inverse Q filter: The Pareto‐Levy stretch." GEOPHYSICS 58, no. 11 (November 1993): 1629–33. http://dx.doi.org/10.1190/1.1443378.

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The seismic impulse response of a constant Q attenuating material has the same mathematical form as the density function for the Pareto‐Levy probability law. Since this law is stable it follows that the seismic pulse is closed under convolution. This means that if the distance from the source x is the sum of two distances [Formula: see text] then the pulse at x is the convolution of the pulse at [Formula: see text] with the one at [Formula: see text]. Its amplitude is proportional to [Formula: see text] where the parameter [Formula: see text] depends only on Q with α = 1 corresponding to a loss‐free material (Q = ∞). As the pulse loses amplitude it stretches along the time axis so that its area is preserved. This scaling between time and distance is illustrated by the stationary phase approximation for the constant Q pulse. The approximation becomes increasingly more accurate for small values of Q until [Formula: see text] where it is exact; it becomes the solution to the heat equation. Log‐stretch inverse Q filtering of seismic data is performed by logarithmically stretching the time axis of the data about a reference time so that all broad‐band pulses have the same shape. A time‐stationary inverse filter is then applied in the stretch domain. However the stretching operation is nonlinear and so band‐limited signals will not have the same shape in the stretch domain—the bandwidths of the stretched wavelets will depend upon wavelet position. To avoid energy loss the bandwidth of the inverse filter must be broader than that of the reference wavelet. For events arriving ahead of the reference wavelet the low‐frequency limit must be lowered, while the high‐frequency limit must be increased for later arrivals. Furthermore, Pareto‐Levy scaling suggests [Formula: see text] stretching corrects the residual traveltime errors that accompany the log‐stretch method of inverse Q filtering.

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47

Liu, Xiao Gang, and Bing Zhao. "Based on the CO₂ Gas Shielded Welding Molten Pool Image Edge Detection Algorithm." Applied Mechanics and Materials 437 (October 2013): 840–44. http://dx.doi.org/10.4028/www.scientific.net/amm.437.840.

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This paper use the passive vision system through high-speed camera collects molten pool images; and then according to the frequency domain characteristics of the weld pool image Butterworth low-pass filter; gradient method for image enhancement obtained after pretreatment. Research Roberts, Sobel, Prewitt, Log, Zerocross, and Canny 6 both traditional differential operator edge detection processing results. Through comparison and analysis of choosing threshold for [0.1, 0. Canny operator can get the ideal molten pool edge character, for subsequent welding molten pool defect recognition provides favorable conditions.

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48

Rector, James W., Spyros K. Lazaratos, Jerry M. Harris, and Mark Van Schaack. "High‐resolution crosswell imaging of a west Texas carbonate reservoir: Part 3—Wavefield separation of reflections." GEOPHYSICS 60, no. 3 (May 1995): 692–701. http://dx.doi.org/10.1190/1.1443808.

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Using crosswell data collected at a depth of about 3000 ft (900 m) in west Texas carbonates, one of the first well‐to‐well reflection images of an oil reservoir was produced. The P and S brute stack reflection images created after wavefield separation tied the sonic logs and exhibited a vertical resolution that was comparable to well log resolution. Both brute stacks demonstrated continuity of several reflectors known to be continuous from log control and also imaged an angular unconformity that was not detected in log correlations or in surface seismic profiling. The brute stacks, particularly the S‐wave reflection image, also exhibited imaging artifacts. We found that multichannel wavefield separation filters that attenuated interfering wavemodes were a critical component in producing high‐resolution reflection images. In this study, the most important elements for an effective wavefield separation were the time‐alignment of seismic arrivals prior to filter application and the implementation of wavefield‐separation filters in multiple domains, particularly in common offset domain. The effectiveness of the multichannel filtering was enhanced through the use of extremely fine wellbore sampling intervals. In this study, 2.5 ft (0.76 m) vertical sampling intervals for both source and receiver were used, whereas most previous crosswell data sets were collected with much coarser sampling intervals, resulting in spatial aliasing and limiting the utility of the data for reflection processing. The wavefield separation techniques employed in this study used data volumes and associated filtering operations that were several orders of magnitude larger than those encountered in conventional VSP data analysis.

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49

Shabestari, Khosrow T., and Fumio Yamazaki. "A Proposal of Instrumental Seismic Intensity Scale Compatible with MMI Evaluated from Three-Component Acceleration Records." Earthquake Spectra 17, no. 4 (November 2001): 711–23. http://dx.doi.org/10.1193/1.1425814.

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Seismic intensity provides useful information on the regional distribution of earthquake effects and has been used to assess seismic hazards and damages. The concept of intensity has been considered as a method to classify severity of the ground motion on the basis of observed effects in the stricken area. In 1996, the Japan Meteorological Agency (JMA) developed a new seismic intensity measurement scale using three-component strong ground motion records in order to provide a measure of the strength of the seismic motion, which is compatible with the existing JMA intensity scale. By applying a band-pass filter to the frequency domain and a vectoral composition of the three components in the time domain, the JMA seismic intensity scale (IJMA) can be calculated without subjective judgement. In this study, we apply the IJMA method to the acceleration records of three recent significant earthquakes in California. For a Modified Mercalli Intensity (MMI) between IV and VIII, a new relation between MMI and log a0, obtained in the process of calculating the new IJMA, is given by the equation MMI=3.93 log a0−1.17. We propose this relation as a new instrumental seismic intensity (IMM) compatible with the California region MMI.

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Dai, Peng, Ing Yann Soon, and Rui Tao. "Direct Recovery of Clean Speech Using a Hybrid Noise Suppression Algorithm for Robust Speech Recognition System." ISRN Signal Processing 2012 (December 26, 2012): 1–9. http://dx.doi.org/10.5402/2012/306305.

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A new log-power domain feature enhancement algorithm named NLPS is developed. It consists of two parts, direct solution of nonlinear system model and log-power subtraction. In contrast to other methods, the proposed algorithm does not need prior speech/noise statistical model. Instead, it works by direct solution of the nonlinear function derived from the speech recognition system. Separate steps are utilized to refine the accuracy of estimated cepstrum by log-power subtraction, which is the second part of the proposed algorithm. The proposed algorithm manages to solve the speech probability distribution function (PDF) discontinuity problem caused by traditional spectral subtraction series algorithms. The effectiveness of the proposed filter is extensively compared using the standard database, AURORA2. The results show that significant improvement can be achieved by incorporating the proposed algorithm. The proposed algorithm reaches a recognition rate of over 86% for noisy speech (average from SNR 0 dB to 20 dB), which means a 48% error reduction over the baseline Mel-frequency Cepstral Coefficient (MFCC) system.

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Journal articles on the topic 'Log-domain filter'

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