To solve the excessive huge scale problem of the traditional multi-bit digital artificial neural network（ANN） hardware implementation methods,a bit-stream ANN hardware implementation method based on sigma delta（Σ...To solve the excessive huge scale problem of the traditional multi-bit digital artificial neural network（ANN） hardware implementation methods,a bit-stream ANN hardware implementation method based on sigma delta（ΣΔ） modulation is presented.The bit-stream adder,multiplier,threshold function unit and fully digital ΣΔ modulator are implemented in a field programmable gate array（FPGA）,and these bit-stream arithmetical units are employed to build the bit-stream artificial neuron.The function of the bit-stream artificial neuron is verified through the realization of the logic function and a linear classifier.The bit-stream perceptron based on the bit-stream artificial neuron with the pre-processed structure is proved to have the ability of nonlinear classification.The FPGA resource utilization of the bit-stream artificial neuron shows that the bit-stream ANN hardware implementation method can significantly reduce the demand of the ANN hardware resources.展开更多
In this paper, new complex band pass filter architecture for continuous time complex band pass sigma delta modulator is presented. In continuation of paper the modulator is designed for GPS and Galileo receiver. This ...In this paper, new complex band pass filter architecture for continuous time complex band pass sigma delta modulator is presented. In continuation of paper the modulator is designed for GPS and Galileo receiver. This modulator was simulated in standard 0.18 μm CMOS TSMC technology and has bandwidth of 2MHz and 4MHz for GPS and Galileo centered in 4.092 MHz. The dynamic range (DR) is 56.5/49 dB (GPS/Galileo) at sampling rate of 125 MHz. The modulator has power consumption of 4.1 mw with 3 V supply voltage.展开更多
基金The National Natural Science Foundation of China (No.60576028)the Natural Science Foundation of Higher Education Institutions of Jiangsu Province(No.11KJB510004)
文摘To solve the excessive huge scale problem of the traditional multi-bit digital artificial neural network（ANN） hardware implementation methods,a bit-stream ANN hardware implementation method based on sigma delta（ΣΔ） modulation is presented.The bit-stream adder,multiplier,threshold function unit and fully digital ΣΔ modulator are implemented in a field programmable gate array（FPGA）,and these bit-stream arithmetical units are employed to build the bit-stream artificial neuron.The function of the bit-stream artificial neuron is verified through the realization of the logic function and a linear classifier.The bit-stream perceptron based on the bit-stream artificial neuron with the pre-processed structure is proved to have the ability of nonlinear classification.The FPGA resource utilization of the bit-stream artificial neuron shows that the bit-stream ANN hardware implementation method can significantly reduce the demand of the ANN hardware resources.
文摘In this paper, new complex band pass filter architecture for continuous time complex band pass sigma delta modulator is presented. In continuation of paper the modulator is designed for GPS and Galileo receiver. This modulator was simulated in standard 0.18 μm CMOS TSMC technology and has bandwidth of 2MHz and 4MHz for GPS and Galileo centered in 4.092 MHz. The dynamic range (DR) is 56.5/49 dB (GPS/Galileo) at sampling rate of 125 MHz. The modulator has power consumption of 4.1 mw with 3 V supply voltage.
