600 Watt Topband Power Amplifier

The photo shows a prototype class D power amplifier using 4 Hexfets in class D operation. Power output is 575W from 24 volt power supply. Input requirement is a few milliwatts. The single turn primary of the 5:1 output transformer is centre tapped and the quad complimentary hexfet pairs alternatively short respective half turns. 24v is therefore alternatively applied to the 1/2 turn putting a maximum voltage of 48v on the hexfet drains. The secondary voltage is a squarewave with maximum peak amplitude Vpeak=i/j x Vcc where i/j is the turns ratio which in this case is 10, and Vcc is 24v. The fundamental frequency component of this squarewave is selected by the o/p filter. Measured values are slightly above theoretical.

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GNU Radio Waterfall and CW Filter

The following GNU radio application adds a waterfall spectrogram to the previous CW filter program. The plot show 4 CW signals in the audio band (lower sideband) at 7023 kHz. The 700Hz signal is filtered and output to the laptop headphones by the CW bandpass filter. The frequency display is shown after the script which is as follows: #!/usr/bin/env python from gnuradio import gr from gnuradio import audio from lpf_bpf_class import Bandpass from gnuradio.qtgui import qtgui from PyQt4 import QtGui import sys, sip class cw_filter(gr.top_block): def __init__(self): gr.top_block.__init__(self) sample_rate = 44100 out_rate = 8000 kaiser = Bandpass() cw_flr = gr.fir_filter_fff(1, kaiser.bpftaps) decimate = int(sample_rate/out_rate) Bandpass.cutoff1 = 3000 pre_decim = Bandpass() dec_flr = gr.fir_filter_fff(1, pre_decim.lpftaps) dec = gr.keep_one_in_n(gr.sizeof_float, decima

Digital Bandpass Filter FIR design - Python

The python code generates the Finite Impulse Response (FIR) filter coefficients for a lowpass filter (LPF) at 10 (Hz) cut off using firwin from scipy. A highpass filter is then created by subtracting the lowpass filter output(s) from the output of an allpass filter. To do this the coefficients of the LPF are multiplied by -1 and 1 added to the centre tap (to create the allpass filter with subtraction). A second LPF is then created with a cutoff at 15 (Hz) and the bandpass filter formed by addition of the LPF and HPF coefficients. The program also generates a test sine wave of a given amplitude and power and to this noise from a Normal distribution is added. The graph below shows the signal and nois, and the signal (green) after filtering. The input snr is approximately 3dB. The frequency response below shows the passband centered on 12.5 (Hz), the Nyquist frequency is 50 (Hz). from numpy import cos, sin, pi, absolute, arange from numpy.random import normal from scipy.

Splunk Cheat Sheet (Linux)

1. set root's password: sudo su passwd root Enter new UNIX password: < new_root_password > Retype new UNIX password: < new_root_password > passwd: password updated successfully # su - 2. Remove any existing Splunk directories & create user etc: # rm -rf /opt/splunkforwarder # userdel -r splunk # this will remove as above if user splunk's home directory # groupadd siem # useradd -g siem -s /bin/bash -d /home/siem -m siem # vi ~/.profile # chage -I -1 -m -0 -M -99999 -E -1 siem If above fails because of multiple passwd fails: # pam_tally --reset check with #chage -l siem # uname -a # check OS version # dpkg -i splunk-4.3.1...........intel.deb # chown -R siem:siem /opt/splunk # su - siem : $SPLUNK_HOME/bin/splunk start --accept-license : $SPLUNK_HOME/bin/splunk edit user admin -password newpassword -role admin -auth admin:changeme 3. vi ~/.profile (as follows) (OR .bash_profile) # ~/.profile: executed by the command interpreter for log

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