Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
February 17, 2026
Neural Networks and Rules-based Systems used to Find Rational and
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A future Wireless communication requires high performance and high speed integrated data, audio, video and multimedia services. This performance is achieved using discrete wavelet transforms in terms of ISI and bandwidth compatibility over FFT based OFDM. Where FFT based OFDM has very compact spectral utilization which cannot satisfy the future needs. This project proposes implementation of new modified lifting wavelet transform for designing wavelets and performing the transform. By implementing LDWT, it is able to increase the spectral efficiency and also decrease the bit error rate. This paper presents a performance measure of mean squared error by using lifting wavelet transform. This paper shows that DWT-OFDM outperformed FFT-OFDM by approximately 6dB gain in BER, Haar wavelet showed best performance over other wavelets by approximately 2dB. However, computation complexity of DWT restricts use of DWT for OFDM due to its hardware requirements on VLSI platform. In this work, lifting based DWT is modified and a new architecture is derived that can compute DWT in less than 3.429ns, and consumes power of less than 28mW.
Dr. Anitha.K. 2012. \u201cModified Lifting Based DWT/IDWT Architecture for OFDM on Virtex-5 FPGA\u201d. Global Journal of Research in Engineering - F: Electrical & Electronic GJRE-F Volume 12 (GJRE Volume 12 Issue F8): .
Crossref Journal DOI 10.17406/gjre
Print ISSN 0975-5861
e-ISSN 2249-4596
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Neural Networks and Rules-based Systems used to Find Rational and
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A future Wireless communication requires high performance and high speed integrated data, audio, video and multimedia services. This performance is achieved using discrete wavelet transforms in terms of ISI and bandwidth compatibility over FFT based OFDM. Where FFT based OFDM has very compact spectral utilization which cannot satisfy the future needs. This project proposes implementation of new modified lifting wavelet transform for designing wavelets and performing the transform. By implementing LDWT, it is able to increase the spectral efficiency and also decrease the bit error rate. This paper presents a performance measure of mean squared error by using lifting wavelet transform. This paper shows that DWT-OFDM outperformed FFT-OFDM by approximately 6dB gain in BER, Haar wavelet showed best performance over other wavelets by approximately 2dB. However, computation complexity of DWT restricts use of DWT for OFDM due to its hardware requirements on VLSI platform. In this work, lifting based DWT is modified and a new architecture is derived that can compute DWT in less than 3.429ns, and consumes power of less than 28mW.
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