November 2012
Intermediate to advanced
794 pages
22h 9m
English
book
Probability, Random Variables, and Random Processes: Theory and Signal Processing Applications
by John J. Shynk
Content preview from Probability, Random Variables, and Random Processes: Theory and Signal Processing Applications
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ABBREVIATIONS
| a.s. | almost surely |
| cdf | cumulative distribution function |
| icdf | inverse of the cdf |
| iid | independent and identically distributed |
| isi | independent and stationary increment |
| probability density function | |
| plim | convergence in probability |
| pmf | probability mass function |
| s. | surely |
| s.t. | subject to |
| w.p.1 | with probability one |
| A | ampere |
| AM | amplitude modulation |
| AOA | angle of arrival |
| AR | autoregressive |
| ARMA | autoregressive moving-average |
| ASK | amplitude shift keying |
| AWGN | additive white Gaussian noise |
| BER | bit error rate |
| BLU | best linear unbiased |
| BPSK | binary phase shift keying |
| BSC | binary symmetric channel |
| CF | characteristic function |
| CGF | cumulant generating function |
| CLT | central limit theorem |
| CM | constant modulus |
| CMA | constant modulus algorithm |
| CMGF | central moment generating function |
| CRLB | Cramér–Rao lower bound |
| dB | decibel |
| DD | decision directed |
| DE | differential equation or difference equation |
| DF | direction finding |
| DFT | discrete Fourier transform |
| DM | Doob-Meyer |
| DTFT | discrete-time Fourier transform |
| EM | expectation maximization |
| F | Farenheit |
| FFT | fast Fourier transform |
| FIR | finite impulse response |
| FM | frequency modulation |
| FMGF | factorial moment generating function |
| FR | forced response |
| FSK | frequency shift keying |
| FSM | finite-state machine |
| GS | Gram–Schmidt |
| Hz | Hertz |
| IIR | infinite impulse response |
| ISI | intersymbol interference |
| KL | Kullback–Leibler |
| KLE | Karhunen–Loève expansion |
| LD | Levinson–Durbin |
| LMF | least-mean fourth |
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