//構造具有指定的標簽的菜單
files = new Menu("文件(F)")
compile = new Menu("編輯(E)")
see = new Menu("查看(V)")
format = new Menu("格式(O)")
font = new Menu("字體和顏色(F)...") //在格式菜單下再添加一個字體及顏色的菜單
help = new Menu("幫助(H)")
//構造具有指定的標簽的菜單項
news = new MenuItem("新建(N)" + " " + "Ctrl+N")
open = new MenuItem("打開(O)..." + " " + "Ctrl+O")
save = new MenuItem("保存(S)" + " " + "Ctrl+S")
other = new MenuItem("另存為(A)...")
page = new MenuItem("頁面設置(U)...")
mim = new MenuItem("打印(P)..." + " " + "Ctrl+P")
quit = new MenuItem("退出(X)")
Computes BER v EbNo curve for convolutional encoding / soft decision
Viterbi decoding scheme assuming BPSK.
Brute force Monte Carlo approach is unsatisfactory (takes too long)
to find the BER curve.
The computation uses a quasi-analytic (QA) technique that relies on the
estimation (approximate one) of the information-bits Weight Enumerating
Function (WEF) using
A simulation of the convolutional encoder. Once the WEF is estimated, the analytic formula for the BER is used.
