Designing a multidimensional digital filter in multidimensional area is a big challenge, especially [[Infinite impulse response|IIR]] filters. Typically it relies on computers to solve difference equations and obtain a set of approximated solutions. While GPGPU computation is becoming popular, several adaptive algorithms have been proposed to design multidimensional [[Finite impulse response|FIR]] and/or [[Infinite impulse response|IIR]] filters by means of GPGPUs.<ref>{{cite journal|title = GPU-efficient Recursive Filtering and Summed-area Tables|url = http://doi.acm.org/10.1145/2024156.2024210|publisher = ACM|journal = Proceedings of the 2011 SIGGRAPH Asia Conference|date = 2011-01-01|___location = New York, NY, USA|isbn = 978-1-4503-0807-6|pages = 176:1–176:12|series = SA '11|doi = 10.1145/2024156.2024210|first = Diego|last = Nehab|first2 = André|last2 = Maximo|first3 = Rodolfo S.|last3 = Lima|first4 = Hugues|last4 = Hoppe}}</ref><ref>{{cite book|title = GPU Gems 2: Programming Techniques For High-Performance Graphics And General-Purpose Computation|last = Pharr|first = Matt|publisher = Pearson Addison Wesley|year = 2005|isbn = 0-321-33559-7|___location = |pages = |last2 = Fernando|first2 = Randima}}</ref><ref>{{cite book|title = GPU Computing Gems Emerald Edition|last = Hwu|first = Wen-mei W.|publisher = Morgan Kaufmann Publishers Inc.|year = 2011|isbn = 0-12-385963-8|___location = San Francisco, CA, USA|pages = }}</ref>
=== Radar Signal Reconstruction and Analysis ===
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=== Self-Driving Car ===
Many [[self-driving cars]] appliesapply 3-D image recognition techniques to auto control the vehicles. Clearly, to accommodate the fast changing exterior environment, the recognition and decision processes must be done in real-time. GPGPUs are excellent devices to achieve the goal.<ref>{{cite journal|title = Accelerating Cost Aggregation for Real-Time Stereo Matching|url = http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6413661|journal = 2012 IEEE 18th International Conference on Parallel and Distributed Systems (ICPADS)|date = 2012-12-01|pages = 472–481|doi = 10.1109/ICPADS.2012.71|first = Jianbin|last = Fang|first2 = A.L.|last2 = Varbanescu|first3 = Jie|last3 = Shen|first4 = H.|last4 = Sips|first5 = G.|last5 = Saygili|first6 = L.|last6 = van der Maaten}}</ref>
=== Medical Image Processing ===
In order to have accurate diagnosis, 2-D or 3-D medical signals, such as [[ultrasound]], [[X-ray]], [[Magnetic resonance imaging|MRI]], and [[CT scan|CT]], often requiresrequire very high sampling rate and image resolutions to reconstruct images. By applying GPGPUs' superior computation power, it haswas been provedshown that we can acquire better-quality on medical images<ref>{{cite web|title = Medical Imaging{{!}}NVIDIA|url = http://www.nvidia.com/object/medical_imaging.html|website = www.nvidia.com|publisher = https://plus.google.com/104889184472622775891|accessdate = 2015-11-07}}</ref><ref>{{cite journal|title = GPU-based Volume Rendering for Medical Image Visualization|url = http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=1615635&url=http%253A%252F%252Fieeexplore.ieee.org%252Fxpls%252Fabs_all.jsp%253Farnumber%253D1615635|journal = Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the|date = 2005-01-01|pages = 5145–5148|doi = 10.1109/IEMBS.2005.1615635|first = Yang|last = Heng|first2 = Lixu|last2 = Gu}}</ref>
