Information theory - 测验
A) Cryptographic use B) Bioinformatics C) Gambling D) Seismic exploration
A) Analog processing methods B) Integrated neural clusters C) High Shannon entropy D) Random seeds external to the software
A) By using semiotic signs B) Through Shannon entropy C) Via digital noise D) Via extractors
A) Min-entropy B) Free energy C) Dynamic core hypothesis D) Effective information
A) Rényi entropy B) Conditional entropy C) Thermal entropy D) Algorithmic entropy
A) In minimizing free energy B) In evaluating randomness in cryptographic systems C) In semiotic code control D) In seismic oil exploration
A) Yes B) No C) Only in cryptographic systems D) Only for pseudorandom numbers
A) Seismic oil exploration B) Black hole analysis C) Bioinformatics D) Search for extraterrestrial intelligence
A) Minimize free energy in the brain B) Strip off and separate unwanted noise from the desired seismic signal C) Decode dominant social messages D) Generate secure pseudorandom numbers
A) Free energy principles B) Extractors and Rényi entropy C) Information theory and digital signal processing D) Cryptographically secure pseudorandom number generators
A) Gerald Edelman and Giulio Tononi B) Umberto Eco and Ferruccio Rossi-Landi C) Karl J. Friston and Andrey Kolmogorov D) Doede Nauta and Winfried Nöth
A) The measurement of sufficient randomness in extractors B) The separation of unwanted noise from seismic signals C) The minimization of free energy in a self-organized system D) The study of the internal processes of coding, filtering, and information processing
A) Gerald Edelman and Karl J. Friston B) Doede Nauta and Winfried Nöth C) C.E. Shannon and R.V.L. Hartley D) Umberto Eco and Ferruccio Rossi-Landi
A) By utilizing cryptographically secure pseudorandom seeds B) By using signs that exhibit a high degree of redundancy C) Through digital signal processing of seismic signals D) By applying the free energy principle
A) To study black holes and bioinformatics B) To extract random numbers for cryptography C) To explore seismic oil deposits D) To analyze the integrated process organization of neural information
A) The issue of seismic noise filtering B) The paradox of extraterrestrial intelligence C) The problem of algorithmic complexity D) The binding problem in cognitive neuroscience
A) R.V.L. Hartley and C.E. Shannon B) Doede Nauta and Winfried Nöth C) Umberto Eco and Ferruccio Rossi-Landi D) Gerald Edelman and Giulio Tononi
A) Min-entropy B) Seismic signal processing C) Effective information D) Shannon entropy
A) Analog methods of data transmission B) A high degree of redundancy in signs C) External cryptographic random seeds D) A reentrant process organization
A) The coding and filtering processes studied in semiotics B) The filtering of unwanted noise from desired seismic signals C) The generation of pseudorandom numbers using extractors D) The synchronization of neurophysiological activity between groups of neuronal populations
A) Charles Sanders Peirce B) Karl J. Friston C) Gerald Edelman D) Giulio Tononi
A) An analog seismic receiver B) A self-organized system C) A dominant social class D) A cryptographic random number generator
A) The integrated information theory B) The Bayesian brain hypothesis C) The semiotic information theory D) The dynamic core hypothesis
A) Astrology B) Alchemy C) Search for extraterrestrial intelligence D) Phrenology
A) Seismic waves B) Tectonic plates C) Black holes D) Neural clusters
A) Biochemistry B) Biomechanics C) Bioinformatics D) Biophysics
A) Cipher creation B) Chess C) Gambling D) Crosswords
A) Gerald Edelman B) Umberto Eco C) R.V.L. Hartley D) Doede Nauta
A) Ferruccio Rossi-Landi B) Giulio Tononi C) Winfried Nöth D) C.E. Shannon
A) Charles Sanders Peirce B) Winfried Nöth C) Karl J. Friston D) Andrey Kolmogorov
A) History of information theory B) Dynamic core hypothesis C) Free energy principle D) Integrated information theory
A) A block cipher B) A brute force attack C) A single organ D) A network
A) Distinct physiological states B) Information theory units C) Symmetric keys D) Unicity distances
A) Why brute force attacks succeed B) How encryption keys are generated C) Why it ceases permanently D) How it occurs
A) Enigma machine interactions B) Cardio-respiratory interactions C) One-time pad interactions D) Cryptographic interactions
A) Cryogenic laboratory environments B) Underground bunker environments C) Extreme environments D) Simulated virtual environments
A) The shannon B) The bit C) The byte D) The ban
A) The Enigma project B) The Ultra project C) The Unicity project D) The Venona project
A) Enigma machine code B) Lorenz cipher code C) One-time pad code D) Symmetric key code
A) It is extremely easy using symmetric keys B) It requires no computational effort C) It is completely impossible under any circumstances D) It is much more difficult than it might first appear
A) An information-theoretic attack B) A brute force attack C) A network physiology attack D) A conditional mutual attack
A) One-time pads B) Asymmetric algorithms C) Secret key algorithms D) Unicity distance algorithms
A) Transfer entropy B) One-time pads C) Block ciphers D) Bans
A) Block ciphers B) Care C) Transfer entropy D) Brute force
A) The Ultra project B) The Venona project C) The Enigma project D) The Network Physiology project
A) Channel coding B) Lossless data compression C) Lossy data compression D) Rate-distortion theory
A) Channel resolvability B) Rate-distortion theory C) Source-channel separation theorems D) Pragmatic information
A) Entropy B) Distortion functions C) Bytes D) Bits
A) The wiretap channel B) The broadcast channel C) The multiple-access channel D) The relay channel
A) The wiretap channel B) The multiple-access channel C) The relay channel D) The broadcast channel
A) The broadcast channel B) The relay channel C) The wiretap channel D) The multiple-access channel
A) Kullback-Leibler divergence B) Cross-entropy C) Mutual information D) Conditional entropy
A) Euclidean space B) Product space C) Vector space D) Metric space
A) log2(pi) B) 1 / pi C) -ln(pi) D) -log2(pi)
A) The geometric mean B) The maximum value C) The weighted average D) The median
A) 1 shannon B) No information C) 2000 bits D) 1000 shannons
A) 1952 B) 1960 C) 1948 D) 1939
A) 1930s B) 1940s C) 1920s D) 1950s
A) Molecular biology B) Quantum computing C) Artificial intelligence D) Telecommunication
A) 0.5 bits B) 1 bit C) Zero D) 2 bits
A) DSL B) Voyager missions C) Compact discs D) ZIP files
A) Artificial intelligence B) Mobile phones C) DSL D) ZIP files
A) Apollo missions B) Voyager missions C) Curiosity rover D) Hubble telescope
A) Television B) Radio C) Steam engine D) Compact disc
A) Automobiles B) Electric guitars C) Mobile phones D) Airplanes
A) The printing press B) The postal service C) The Internet D) The telegraph network
A) Optical computing B) Cloud computing C) Distributed computing D) Quantum computing
A) Architectural drafting B) Art creation C) Oil painting restoration D) Sculpture casting
A) Music B) Vocal cord anatomy C) Musical instrument design D) Acoustic room resonance
A) Aesthetics B) Ethics C) Epistemology D) Metaphysics
A) Vannevar Bush B) James Gleick C) Ralph Hartley D) Harry Nyquist
A) 1940 B) 1939 C) 1948 D) 1928
A) Alan Turing B) Ludwig Boltzmann C) Vannevar Bush D) James Gleick
A) Ralph Hartley B) Harry Nyquist C) Alan Turing D) Claude Shannon
A) W = K log m B) E = mc2 C) H = log Sn D) PV = nRT
A) The byte B) The baud C) The bit D) The decimal digit
A) Claude Shannon B) Harry Nyquist C) Ralph Hartley D) Alan Turing
A) Rolf Landauer B) James Gleick C) Vannevar Bush D) Harry Nyquist
A) Binary logarithm B) Common logarithm C) Decimal logarithm D) Natural logarithm
A) Base-two logarithm B) Natural logarithm C) Common logarithm D) Binary logarithm
A) Common logarithm B) Natural logarithm C) Binary logarithm D) Base-e logarithm
A) The lowest possible information content B) The most unpredictable state C) The most predictable state D) A deterministic sequence
A) Base-256 B) Base-10 C) Base-e D) Base-2
A) A Markov trial B) An equiprobable trial C) A Bernoulli trial D) A logarithmic trial
A) Equivocation B) Marginal entropy C) Joint entropy D) Mutual information
A) Transinformation B) Kullback-Leibler divergence C) Pointwise mutual information D) Log-likelihood ratio
A) Communication B) Macroeconomics C) Thermodynamics D) Quantum mechanics
A) Jensen-Shannon divergence B) Mahalanobis distance C) Kullback-Leibler divergence D) Euclidean distance
A) Student's t-test B) Mann-Whitney U test C) Shapiro-Wilk test D) Log-likelihood ratio test
A) Euclidean metric B) Linear transformation C) Inner product D) Semi-quasimetric
A) Both B) Alice C) Neither D) Bob
A) It is impossible to determine B) Alice C) Both will be equally surprised D) Bob
A) An infinite continuous set B) A discrete set C) An empty set D) A finite geometric set
A) Only in quantum states B) Only in macroscopic mechanics C) Yes D) No
A) {X0, X1, ..., X_{n-1}} B) {Y1, Y2, ..., Y_n} C) {X1, Y1, ..., X_n, Y_n} D) {X1, X2, ..., X_n}
A) A result of zero B) An undefined value C) The same result D) Completely different results
A) An inherent fixed property B) An unpredictable random variable that changes constantly C) A negligible factor in modern systems D) A completely controllable variable
A) Hb B) i C) e D) p
A) Duplicates the input bit B) Erases the input bit C) Delays the input bit D) Flips the input bit
A) Memory B) Gaussian noise C) Zero capacity D) Ternary input |
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