SNLSDP version 0 -- a MATLAB software for sensor network localization It implemented an SDP based approach with regularization for solving sensor network localization problems. The algorithm first solves an SDP relaxation (with regularization) of the non-convex minimization problem (1), and use the SDP computed solution as the starting point for a gradient descent method with backtracking line search to solve the smooth unconstrained problem (2). This software package is designed for solving small size senor network localization problems with up to 200 sensors and a few thousands given distances. (Source:

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  1. D’Ambrosio, Claudia; Vu, Ky; Lavor, Carlile; Liberti, Leo; Maculan, Nelson: New error measures and methods for realizing protein graphs from distance data (2017)
  2. Ding, Chao; Qi, Hou-Duo: Convex optimization learning of faithful Euclidean distance representations in nonlinear dimensionality reduction (2017)
  3. Hu, Yaohua; Li, Chong; Yang, Xiaoqi: On convergence rates of linearized proximal algorithms for convex composite optimization with applications (2016)
  4. Qi, Hou-Duo; Yuan, Xiaoming: Computing the nearest Euclidean distance matrix with low embedding dimensions (2014)
  5. Wu, Changzhi; Li, Chaojie; Long, Qiang: A DC programming approach for sensor network localization with uncertainties in anchor positions (2014)
  6. Cucuringu, Mihai: ASAP: an eigenvector synchronization algorithm for the graph realization problem (2013)
  7. Fang, Xingyuan; Toh, Kim-Chuan: Using a distributed SDP approach to solve simulated protein molecular conformation problems (2013)
  8. Jia, Jie; Zhang, Guiyuan; Wang, Xingwei; Chen, Jian: On distributed localization for road sensor networks: a game theoretic approach (2013)
  9. Manjarres, Diana; Del Ser, Javier; Gil-Lopez, Sergio; Vecchio, Massimo; Landa-Torres, Itziar; Lopez-Valcarce, Roberto: A novel heuristic approach for distance- and connectivity-based multihop node localization in wireless sensor networks (2013) ioport
  10. Lavor, Carlile; Liberti, Leo; Maculan, Nelson; Mucherino, Antonio: The discretizable molecular distance geometry problem (2012)
  11. Pong, Ting Kei: Edge-based semidefinite programming relaxation of sensor network localization with lower bound constraints (2012)
  12. Alfakih, Abdo Y.; Anjos, Miguel F.; Piccialli, Veronica; Wolkowicz, Henry: Euclidean distance matrices, semidefinite programming and sensor network localization (2011)
  13. Pong, Ting Kei; Tseng, Paul: (Robust) edge-based semidefinite programming relaxation of sensor network localization (2011)
  14. Singer, A.: Angular synchronization by eigenvectors and semidefinite programming (2011)
  15. Ding, Yichuan; Krislock, Nathan; Qian, Jiawei; Wolkowicz, Henry: Sensor network localization, Euclidean distance matrix completions, and graph realization (2010)
  16. Ruan, N.; Gao, David Y.; Jiao, Y.: Canonical dual least square method for solving general nonlinear systems of quadratic equations (2010)
  17. Tseng, Paul: Approximation accuracy, gradient methods, and error bound for structured convex optimization (2010)
  18. Kim, Sunyoung; Kojima, Masakazu; Waki, Hayato: Exploiting sparsity in SDP relaxation for sensor network localization (2009)
  19. Nie, Jiawang: Sum of squares method for sensor network localization (2009)
  20. Biswas, Pratik; Toh, Kim-Chuan; Ye, Yinyu: A distributed SDP approach for large-scale noisy anchor-free graph realization with applications to molecular conformation (2008)

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