2 x 813 HF Linear Restoration part 1

The first steps in restoring and updating the old G2DAF linear amplifier commenced with the removal of the 2 x 6U4GT rectifier valves and the associated voltage doubler components / 300 ohm input circuit. This will be replaced with a solid state voltage doubler (probably a 1N4148 diode stack) and a 1:4 unun broadband transformer to give as close a match to 50 ohms as possible. Next step was to solder a 5000 ohm resistor from the 813 anodes to ground. Two 10k resistors in parallel were used (see photo) to represent the load that the valves should see under normal operation. An MFJ antenna analyser was then connected to the pi - tank output and the variable capacitors in the tank circuit altered until a 1:1 50 ohm match was obtained on 80m and on 10m. This checked the output matching circuit.

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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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