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Karmeshu
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2020 – today
- 2022
- [j32]Shachi Sharma
, Parag C. Pendharkar
, Karmeshu
:
Learning Component Size Distributions for Software Cost Estimation: Models Based on Arithmetic and Shifted Geometric Means Rules. IEEE Trans. Software Eng. 48(12): 5136-5147 (2022) - [d1]Shachi Sharma, Parag C. Pendharkar, Karmeshu:
Software Component Size Dataset. IEEE DataPort, 2022
2010 – 2019
- 2019
- [j31]Santosh Kumar
, Rajeev Kumar Singh
, Karmeshu:
Exact distributions for bit error rate and channel capacity in free-space optical communication. IET Commun. 13(18): 2966-2972 (2019) - [j30]Sanjeev Patel
, Karmeshu:
A New Modified Dropping Function for Congested AQM Networks. Wirel. Pers. Commun. 104(1): 37-55 (2019) - 2018
- [j29]Sanjeev Kumar, Karmeshu:
Characterizing ISI and sub-threshold membrane potential distributions: Ensemble of IF neurons with random squared-noise intensity. Biosyst. 166: 43-49 (2018) - [j28]Rajeev Kumar Singh
, Santosh Kumar
, Karmeshu:
New approximation for pdf of K- distribution: analytical study of QoS parameters in free space optical communication. IET Commun. 12(14): 1703-1708 (2018) - [j27]Sanjeev Patel
, Kanwar Sen, Karmeshu:
Performance Analysis of AQM Scheme Using Factorial Design Framework. IEEE Syst. J. 12(2): 1211-1218 (2018) - [j26]Shalabh Bhatnagar
, Sanjeev Patel
, Karmeshu:
A stochastic approximation approach to active queue management. Telecommun. Syst. 68(1): 89-104 (2018) - 2017
- [j25]Karmeshu, Sanjeev Patel
, Shalabh Bhatnagar
:
Adaptive mean queue size and its rate of change: queue management with random dropping. Telecommun. Syst. 65(2): 281-295 (2017) - 2016
- [j24]Dilip Senapati, Karmeshu:
Generation of cubic power-law for high frequency intra-day returns: Maximum Tsallis entropy framework. Digit. Signal Process. 48: 276-284 (2016) - [i2]Karmeshu, Sanjeev Patel, Shalabh Bhatnagar:
Adaptive Mean Queue Size and Its Rate of Change: Queue Management with Random Dropping. CoRR abs/1602.02241 (2016) - 2015
- [j23]Abhinav Gupta
, Karmeshu:
Study of compound generalized Nakagami-generalized inverse Gaussian distribution and related densities: application to ultrasound imaging. Comput. Stat. 30(1): 81-96 (2015) - [j22]Amit Kumar Singh, Harendra Pratap Singh, Karmeshu:
Analysis of Finite Buffer Queue: Maximum Entropy Probability Distribution With Shifted Fractional Geometric and Arithmetic Means. IEEE Commun. Lett. 19(2): 163-166 (2015) - [j21]Abhinav Gupta
, Karmeshu:
Efficacy of Pearson distributions for characterization of gray levels in clinical ultrasound kidney images. Signal Image Video Process. 9(6): 1317-1334 (2015) - [j20]Vineet Khandelwal, Karmeshu:
Channel Capacity Analysis over Slow Fading Environment: Unified Truncated Moment Generating Function Approach. Wirel. Pers. Commun. 82(4): 2377-2390 (2015) - [c3]Karmeshu, Shachi Sharma, Sanjeev Kumar:
Generation of Power Law: Maximum Entropy Framework and Superstatistics. ICMMI 2015: 45-59 - 2014
- [j19]Amit Kumar Singh, Karmeshu:
Power Law Behavior of Queue Size: Maximum Entropy Principle with Shifted Geometric Mean Constraint. IEEE Commun. Lett. 18(8): 1335-1338 (2014) - [j18]Vineet Khandelwal, Karmeshu:
A New Approximation for Average Symbol Error Probability over Log-Normal Channels. IEEE Wirel. Commun. Lett. 3(1): 58-61 (2014) - [j17]Vineet Khandelwal, Karmeshu:
Performance Analysis of Composite Fading Channel Based on Point Estimate Method. Wirel. Pers. Commun. 79(2): 953-968 (2014) - 2013
- [j16]Karmeshu, Vineet Khandelwal:
On the Applicability of Average Channel Capacity in Log-Normal Fading Environment. Wirel. Pers. Commun. 68(4): 1393-1402 (2013) - 2011
- [j15]Karmeshu, Varun Gupta, K. V. Kadambari:
Neuronal model with distributed delay: analysis and simulation study for gamma distribution memory kernel. Biol. Cybern. 104(6): 369-383 (2011) - [j14]Karmeshu, Shalabh Bhatnagar
, Vivek Kumar Mishra:
An Optimized SDE Model for Slotted Aloha. IEEE Trans. Commun. 59(6): 1502-1508 (2011) - [c2]Karmeshu, Vineet Khandelwal:
MGF and high order moment of channel capacity in log-normal fading environment. ACWR 2011: 99-106 - 2010
- [i1]Karmeshu, Shachi Sharma:
Long Tail Behavior of Queue Lengths in Broadband Networks: Tsallis Entropy Framework. CoRR abs/1012.2464 (2010)
2000 – 2009
- 2009
- [j13]Shachi Sharma, Karmeshu:
Power law characteristics and loss probability: finite buffer queueing systems. IEEE Commun. Lett. 13(12): 971-973 (2009) - [j12]Shalabh Bhatnagar
, Karmeshu, Vivek Kumar Mishra:
Optimal parameter trajectory estimation in parameterized SDEs: An algorithmic procedure. ACM Trans. Model. Comput. Simul. 19(2): 8:1-8:27 (2009) - 2008
- [j11]R. K. Agrawal
, Karmeshu:
Perturbation scheme for online learning of features: Incremental principal component analysis. Pattern Recognit. 41(5): 1452-1460 (2008) - [j10]Shachi Sharma, Karmeshu:
Bimodal packet distribution in loss systems using maximum Tsallis entropy principle. IEEE Trans. Commun. 56(9): 1530-1535 (2008) - [j9]Karmeshu, Debasree Goswami:
Transient Bimodality and Catastrophic Jumps in Innovation Diffusion. IEEE Trans. Syst. Man Cybern. Part A 38(3): 644-654 (2008) - 2007
- [j8]Rajeev Agrawal
, Karmeshu:
Ultrasonic backscattering in tissue: characterization through Nakagami-generalized inverse Gaussian distribution. Comput. Biol. Medicine 37(2): 166-172 (2007) - [j7]Karmeshu, Praveen Sharma:
Truncating the hierarchy of moment equations based on point distribution - application to innovation diffusion. Math. Comput. Model. 45(3-4): 233-240 (2007) - [j6]Karmeshu, Rajeev Agrawal
:
On efficacy of Rayleigh-inverse Gaussian distribution over K-distribution for wireless fading channels. Wirel. Commun. Mob. Comput. 7(1): 1-7 (2007) - 2006
- [j5]Karmeshu, Shachi Sharma:
Queue length distribution of network packet traffic: Tsallis entropy maximization with fractional moments. IEEE Commun. Lett. 10(1): 34-36 (2006) - [j4]Karmeshu, Shachi Sharma:
q-Exponential product-form solution of packet distribution in queueing networks: maximization of Tsallis entropy. IEEE Commun. Lett. 10(8): 585-587 (2006) - [j3]Nikhil R. Pal, Animesh Sharma, Somitra Kumar Sanadhya
, Karmeshu:
On identifying marker genes from gene expression data in a neural framework through online feature analysis. Int. J. Intell. Syst. 21(4): 453-467 (2006) - 2004
- [c1]Karmeshu, A. Krishnamachari:
Sequence Variability and Long-Range Dependence in DNA: An Information Theoretic Perspective. ICONIP 2004: 1354-1361 - 2001
- [j2]Werner Ebeling, Karmeshu, Andrea Scharnhorst:
Dynamics of Economic and Technological Search Processes in Complex Adaptive Landscapes. Adv. Complex Syst. 4(1): 71-88 (2001)
1980 – 1989
- 1984
- [j1]Karmeshu, N. C. Lind, V. Cano:
Rationales for Bradford's law. Scientometrics 6(4): 233-241 (1984)
Coauthor Index
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