This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.
Sanei S, Chambers JA. EEG Signal Processing, 1. ed. Wiley Interscience: New York. 2007. http://dx.doi.org/10.1002/9780470511923SaneiSChambersJAEEG Signal Processing, 1. edWiley InterscienceNew York2007http://dx.doi.org/10.1002/978047051192310.1002/9780470511923Search in Google Scholar
Michel CM, Murray MM, Lantz G, Gonzalez S, Spinelli L, Grave de Peralta R. EEG source imaging. Clin. Neurophysiol. 2004;115(10):2195-2222. http://dx.doi.org/10.1016/j.clinph.2004.06.0011535136110.1016/j.clinph.2004.06.001MichelCMMurrayMMLantzGGonzalezSSpinelliLGrave de PeraltaREEG source imagingClin. Neurophysiol2004115102195–2222http://dx.doi.org/10.1016/j.clinph.2004.06.00115351361Search in Google Scholar
Argyropoulos S, Tzovaras D, Ioannidis D, Damousis Y, Braun M, Boverie S, et al. Biometric template security in multimodal biometric systems based on error correcting codes. Journal of Computer Securit. 2010;18(1):161–185.10.3233/JCS-2010-0369ArgyropoulosSTzovarasDIoannidisDDamousisYBraunMBoverieSet alBiometric template security in multimodal biometric systems based on error correcting codesJournal of Computer Securit2010181161–185Open DOISearch in Google Scholar
Scher MS. Automated EEG-sleep analyses and neonatal neurointensive care. Sleep Medicine. 2004;5(6):533-40. http://dx.doi.org/10.1016/j.sleep.2004.07.00210.1016/j.sleep.2004.07.00215511699ScherMSAutomated EEG-sleep analyses and neonatal neurointensive careSleep Medicine200456533–40http://dx.doi.org/10.1016/j.sleep.2004.07.00215511699Open DOISearch in Google Scholar
Abaya EF, Wise GL. On the Existence of optimal quantizers. IEEE Trans. Information Theory. 1982;28(6);937-940. http://dx.doi.org/10.1109/TIT.1982.105658210.1109/TIT.1982.1056582AbayaEFWiseGLOn the Existence of optimal quantizersIEEE Trans. Information Theory1982286937–940http://dx.doi.org/10.1109/TIT.1982.1056582Open DOISearch in Google Scholar
Tolbert JR, Kabali P, Brar S, Mukhopadhyay S. A low power system with adaptive data compression for wireless monitoring of physiological signals and its application to wireless electroencephalograph.11. International Symposium on Quality Electronic Design (ISQED), San Jose, CA. USA. 2010:333-341.TolbertJRKabaliPBrarSMukhopadhyaySA low power system with adaptive data compression for wireless monitoring of physiological signals and its application to wireless electroencephalograph.11International Symposium on Quality Electronic Design (ISQED), San Jose, CA. USA2010333–34110.1109/ISQED.2010.5450552Search in Google Scholar
Yates DC. A key power trade-off in wireless EEG headset design. IEEE EMBS Conference on Neural Engineering. 2007:453-456. http://dx.doi.org/10.1109/CNE.2007.369707YatesDCA key power trade-off in wireless EEG headset designIEEE EMBS Conference on Neural Engineering2007453–456http://dx.doi.org/10.1109/CNE.2007.36970710.1109/CNE.2007.369707Search in Google Scholar
Wang A, Sodini C. A simple energy model for wireless micro sensor transceivers. IEEE Global Telecomm Conf., Texas, USA. 2005:3205-3209.WangASodiniCA simple energy model for wireless micro sensor transceiversIEEE Global Telecomm Conf., TexasUSA20053205–3209Search in Google Scholar
Lin CT, Chen YC, Huang Y, Chiu TT, Ko LW, Liang SF, et al. Development of wireless brain computer interface with embedded multitask scheduling and its application on real-time driver's drowsiness detection and warning. IEEE Trans. Biomed. Eng. 2008;55(5):1582-1591. http://dx.doi.org/10.1109/TBME.2008.9185661844090410.1109/TBME.2008.918566LinCTChenYCHuangYChiuTTKoLWLiangSFet alDevelopment of wireless brain computer interface with embedded multitask scheduling and its application on real-time driver's drowsiness detection and warningIEEE Trans. Biomed. Eng20085551582–1591http://dx.doi.org/10.1109/TBME.2008.91856618440904Search in Google Scholar
Sayood K. Introduction to data compression. 3. ed. Elsevier: NewYork. 2006.SayoodKIntroduction to data compression. 3. edElsevierNewYork200610.1016/B978-012620862-7/50018-3Search in Google Scholar
Bao X, Wang J, Hu J. Method of individual identification based on electroencephalogram analysis. International Conference on New Trends in Information and Service Science. 2009:390-393.BaoXWangJHuJMethod of individual identification based on electroencephalogram analysisInternational Conference on New Trends in Information and Service Science2009390–39310.1109/NISS.2009.44Search in Google Scholar
Jayant N. Adaptive quantization with one word memory. The Journal of the Acoustical Society of America. 1973;54(3):340. http://dx.doi.org/10.1121/1.197838110.1121/1.1978381JayantNAdaptive quantization with one word memoryThe Journal of the Acoustical Society of America1973543340http://dx.doi.org/10.1121/1.1978381Open DOISearch in Google Scholar
Mitra D. Mathematical analysis of an adaptive quantizer. Bell Systems Technical Journal. 1974, 53(5), 867-898. http://dx.doi.org/10.1002/j.1538-7305.1974.tb02774.x10.1002/j.1538-7305.1974.tb02774.xMitraDMathematical analysis of an adaptive quantizerBell Systems Technical Journal1974535867–898http://dx.doi.org/10.1002/j.1538-7305.1974.tb02774.xOpen DOISearch in Google Scholar
Sayood K, Gibson JD. Explicit additive noise models for uniform and nonuniform MMSE quantization. Signal Processing Journal. 1984;7(4):407-414. http://dx.doi.org/10.1016/0165-1684(84)90038-010.1016/0165-1684(84)90038-0SayoodKGibsonJDExplicit additive noise models for uniform and nonuniform MMSE quantizationSignal Processing Journal198474407–414http://dx.doi.org/10.1016/0165-1684(84)90038-0Open DOISearch in Google Scholar
Sayood K, Na S. Recursively indexed quantization of memoryless sources. IEEE Transactions on Information Theory. 1996;38(5):1602-1609. http://dx.doi.org/10.1109/18.149516SayoodKNaSRecursively indexed quantization of memoryless sourcesIEEE Transactions on Information Theory19963851602–1609http://dx.doi.org/10.1109/18.14951610.1109/18.149516Search in Google Scholar
Farvardin N, Modestino JW. Optimum quantizer Performance for a class of non-Gaussian memoryless sources, IEEE Transactions on Information Theory. 1984;30(3):485-497. http://dx.doi.org/10.1109/TIT.1984.105692010.1109/TIT.1984.1056920FarvardinNModestinoJWOptimum quantizer Performance for a class of non-Gaussian memoryless sourcesIEEE Transactions on Information Theory1984303485–497http://dx.doi.org/10.1109/TIT.1984.1056920Open DOISearch in Google Scholar
Julius OS. Mathematics of the discrete Fourier Transform (DFT). 2. ed. W3K Publishing.2007.JuliusOSMathematics of the discrete Fourier Transform (DFT)2007Search in Google Scholar
Glover IA, Grant PM. Digital Communications. New Jersey: Prentice Hall. 1998.GloverIAGrantPMDigital CommunicationsNew JerseyPrentice Hall1998Search in Google Scholar
Abdullah MK, Subari KS, Loong JLCH, Ahmad NN. Analysis of the EEG signal for a practical biometric system. World Academy of Science, Engineering and Technology. 2010;(68):1133-1137.AbdullahMKSubariKSLoongJLCHAhmadNNAnalysis of the EEG signal for a practical biometric systemWorld Academy of Science, Engineering and Technology2010681133–1137Search in Google Scholar
Chi M, Wang Y, Maier C, Jung TP, Cauwenberghs G. Dry and noncontact EEG sensors for mobile brain–computer interfaces. IEEE Trans. Neural Systems and Rehab. Eng. 201220228–235. http://dx.doi.org/10.1109/TNSRE.2011.217465210.1109/TNSRE.2011.2174652ChiMWangYMaierCJungTPCauwenberghsGDry and noncontact EEG sensors for mobile brain–computer interfacesIEEE Trans. Neural Systems and Rehab. Eng201220228–235http://dx.doi.org/10.1109/TNSRE.2011.217465222180514Open DOISearch in Google Scholar
Zhang Z, Jung TP. Compressed sensing of EEG for wireless telemonitoring with low energy consumption and inexpensive hardware. IEEE Trans. Biomed. Eng. 2013;60(1):221-224. http://dx.doi.org/10.1109/TBME.2012.221795910.1109/TBME.2012.221795922968206ZhangZJungTPCompressed sensing of EEG for wireless telemonitoring with low energy consumption and inexpensive hardwareIEEE Trans. Biomed. Eng2013601221–224http://dx.doi.org/10.1109/TBME.2012.221795922968206Open DOISearch in Google Scholar
Callan D, Gamez M, Cassel D, Terzibas C, Callan A, Kawato M, et alDynamic visuomotor transformation involved with remote flying of a plane utilizes the 'Mirror Neuron' system. PLoS One. 2012;7:1-14. http://dx.doi.org/10.1371/journal.pone.0033873CallanDGamezMCasselDTerzibasCCallanAKawatoMet alDynamic visuomotor transformation involved with remote flying of a plane utilizes the 'Mirror Neuron' systemPLoS One201271–14http://dx.doi.org/10.1371/journal.pone.003387310.1371/journal.pone.0033873333503722536320Search in Google Scholar
Marcel S, Millan J. Person authentication using brainwaves (EEG) and maximum a posteriori model adaptation. IEEE Trans. Pattern Analysis and Machine Intelligence. 2012;29(4):743-750. http://dx.doi.org/10.1109/TPAMI.2007.1012MarcelSMillanJPerson authentication using brainwaves (EEG) and maximum a posteriori model adaptationIEEE Trans. Pattern Analysis and Machine Intelligence2012294743–750http://dx.doi.org/10.1109/TPAMI.2007.101210.1109/TPAMI.2007.101217299229Search in Google Scholar
Palaniappan R, Mandic DP. Biometrics from brain electrical activity. A machine learning approach. IEEE Trans. Pattern Analysis and Machine Intelligence. 2007;29:738-742. http://dx.doi.org/10.1109/TPAMI.2007.101310.1109/TPAMI.2007.1013PalaniappanRMandicDPBiometrics from brain electrical activity. A machine learning approach. IEEE TransPattern Analysis and Machine Intelligence200729738–742http://dx.doi.org/10.1109/TPAMI.2007.101317299228Open DOISearch in Google Scholar
Palaniappan R,Mandic DP. EEG based biometric framework for automatic identity verification. Journal of VLSI Signal Processing Systems. 2007;49(2):243-250.10.1007/s11265-007-0078-1PalaniappanRMandicDPEEG based biometric framework for automatic identity verificationJournal of VLSI Signal Processing Systems2007492243–250Open DOISearch in Google Scholar
Usakli AB. Improvement of EEG signal acquisition: An Electrical Aspect for State of the Art of Front End. Computational Intelligence and Neuroscience. 2010; 630649, 7 pages. http://dx.doi.org/10.1155/2010/630649UsakliABImprovement of EEG signal acquisition: An Electrical Aspect for State of the Art of Front EndComputational Intelligence and Neuroscience20107http://dx.doi.org/10.1155/2010/63064910.1155/2010/630649Search in Google Scholar
Marks RJ. Introduction to Shannon Sampling and Interpolation Theory, Spinger-Verlag. 1991. http://dx.doi.org/10.1007/978-1-4613-9708-3MarksRJIntroduction to Shannon Sampling and Interpolation TheorySpinger-Verlag1991http://dx.doi.org/10.1007/978-1-4613-9708-310.1007/978-1-4613-9708-3Search in Google Scholar
Tong S, Bezerianos A, Paul J, Zhu Y, Thakor N. Nonextensive entropy measure of EEG following brain injury from cardiac arrest. Journal of Statistical Mechanics and its Applications.2002;305(15):619-625. http://dx.doi.org/10.1016/S0378-4371(01)00621-510.1016/S0378-4371(01)00621-5TongSBezerianosAPaulJZhuYThakorNNonextensive entropy measure of EEG following brain injury from cardiac arrestJournal of Statistical Mechanics and its Applications200230515619–625http://dx.doi.org/10.1016/S0378-4371(01)00621-5Open DOISearch in Google Scholar