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Articles by A. Sivasubramanian
Total Records ( 2 ) for A. Sivasubramanian
  Sharmila Hemanandh and A. Sivasubramanian
  This study describes Fast Fourier Transform implementation using fused floating point operations in parallel fashion. The Fast Fourier Transform processors use butterfly unit for computations on complex data. These operations are performed by FFT processors using complex butterfly operations that consist of multiplication, addition and subtraction operations. The main contribution in this research includes a radix-8 butterfly unit with higher efficiency. Also this butterfly unit performs faster than the conventional butterfly. The area required is reduced with the use of FFT Floating Point Butterfly unit as compared to the conventional butterfly unit. The complete architecture is synthesized and simulated using Xilinx ISE Software. The comparison of our proposed method with similar FFT architecture using radix-4 exhibited about 26.36% reduction in area and about 50.22% reduction in overall power consumption.
  A. Sivasubramanian and V.C. Ravichandran
  In long haul networks, the random birefringence induced in the optical fiber leads to a considerable Polarization Mode Dispersion (PMD). Polarization Dependent Loss (PDL) mainly occurs in optical components and depends on the state of polarization of optical signals. The presence of PMD and PDL causes pulsewidth narrowing and the pulsewidth reduction depends on states of polarization at which the input light launched and also the input pulsewidth. A system comprising of a PDL element sandwiched between two PMD elements was considered. This system was characterized using neural network approach. Back propagation algorithm was applied to train the network with four input vectors namely PMD, PDL, input pulsewidth and the angle describing the input states of polarization and one output vector indicating effective squared pulsewidth difference. On analysis, it was found that the pulsewidth reduction was higher for a PMD of 30ps, a PDL of 3.5 and input pulsewidth of 100ps at various (Linear and Circular) input states of polarization with the angle describing the input state of polarization to be |π/4|. Similarly, for a given value of PMD, PDL, input pulsewidth and a specific pulsewidth reduction, the input state of polarization at which the light was to be launched can also be determined using neural network approach.
 
 
 
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