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Probability and random processes [[electronic resource] ] : with applications to signal processing and communications / / Scott L. Miller, Donald Childers
Probability and random processes [[electronic resource] ] : with applications to signal processing and communications / / Scott L. Miller, Donald Childers
Autore Miller Scott L
Edizione [Ed. 2.]
Pubbl/distr/stampa Waltham, Mass., : Elsevier, 2012
Descrizione fisica 1 online resource (625 p.)
Disciplina 621.382/20151
Altri autori (Persone) ChildersDonald G
Soggetto topico Signal processing - Mathematics
Probabilities
Stochastic processes
Soggetto genere / forma Electronic books.
ISBN 1-283-41027-3
9786613410276
0-12-387013-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Front Cover; Probability and Random Processes: With Applications to Signal Processingand Communications; Copyright; Contents; Preface; Chapter 1: Introduction; 1.1 A Speech Recognition System; 1.2 A Radar System; 1.3 A Communication Network; Chapter 2: Introduction to Probability Theory; 2.1 Experiments, Sample Spaces, and Events; 2.2 Axioms of Probability; 2.3 Assigning Probabilities; 2.4 Joint and Conditional Probabilities; 2.5 Basic Combinatorics; 2.6 Bayes's Theorem; 2.7 Independence; 2.8 Discrete Random Variables; 2.9 Engineering Application-An Optical Communication System; Exercises
Section 2.1: Experiments, Sample Spaces, and EventsSection 2.2: Axioms of Probability; Section 2.3: Assigning Probabilities; Section 2.4: Joint and Conditional Probabilities; Section 2.5: Basic Combinatorics; Section 2.6: Bayes's Theorem; Section 2.7: Independence; Section 2.8: Discrete Random Variables; Miscellaneous Problems; MATLAB Exercises; Chapter 3: Random Variables, Distributions,and Density Functions; 3.1 The Cumulative Distribution Function; 3.2 The Probability Density Function; 3.3 The Gaussian Random Variable; 3.4 Other Important Random Variables; 3.4.1 Uniform Random Variable
3.4.2 Exponential Random Variable3.4.3 Laplace Random Variable; 3.4.4 Gamma Random Variable; 3.4.5 Erlang Random Variable; 3.4.6 Chi-Squared Random Variable; 3.4.7 Rayleigh Random Variable; 3.4.8 Rician Random Variable; 3.4.9 Cauchy Random Variable; 3.5 Conditional Distribution and Density Functions; 3.6 Engineering Application: Reliability and Failure Rates; Exercises; Section 3.1: The Cumulative Distribution Function; Section 3.2: The Probability Density Function; Section 3.3: The Gaussian Random Variable; Section 3.4: Other Important Random Variables
Section 3.5: Conditional Distribution and Density FunctionsSection 3.6: Reliability and Failure Rates; Miscellaneous Exercises; MATLAB Exercises; Chapter 4: Operations on a Single Random Variable; 4.1 Expected Value of a Random Variable; 4.2 Expected Values of Functions of Random Variables; 4.3 Moments; 4.4 Central Moments; 4.5 Conditional Expected Values; 4.6 Transformations of Random Variables; 4.6.1 Monotonically Increasing Functions; 4.6.2 Monotonically Decreasing Functions; 4.6.3 Nonmonotonic Functions; 4.7. Characteristic Functions; 4.8. Probability-Generating Functions
4.9 Moment-Generating Functions4.10 Evaluating Tail Probabilities; 4.11 Engineering Application-Scalar Quantization; 4.12 Engineering Application-Entropy and Source Coding; Exercises; Section 4.1: Expected Values of a Random Variable; Section 4.2: Expected Values of Functions of a Random Variable; Section 4.3: Moments; Section 4.4: Central Moments; Section 4.5: Conditional Expected Values; Section 4.6: Transformations of Random Variables; Section 4.7: Characteristic Functions; Section 4.8: Probability-Generating Functions; Section 4.9: Moment-Generating Functions
Section 4.10: Evaluating Tail Probabilities
Record Nr. UNINA-9910458157803321
Miller Scott L  
Waltham, Mass., : Elsevier, 2012
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Probability and random processes [[electronic resource] ] : with applications to signal processing and communications / / Scott L. Miller, Donald Childers
Probability and random processes [[electronic resource] ] : with applications to signal processing and communications / / Scott L. Miller, Donald Childers
Autore Miller Scott L
Edizione [Ed. 2.]
Pubbl/distr/stampa Waltham, Mass., : Elsevier, 2012
Descrizione fisica 1 online resource (625 p.)
Disciplina 621.382/20151
Altri autori (Persone) ChildersDonald G
Soggetto topico Signal processing - Mathematics
Probabilities
Stochastic processes
ISBN 1-283-41027-3
9786613410276
0-12-387013-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Front Cover; Probability and Random Processes: With Applications to Signal Processingand Communications; Copyright; Contents; Preface; Chapter 1: Introduction; 1.1 A Speech Recognition System; 1.2 A Radar System; 1.3 A Communication Network; Chapter 2: Introduction to Probability Theory; 2.1 Experiments, Sample Spaces, and Events; 2.2 Axioms of Probability; 2.3 Assigning Probabilities; 2.4 Joint and Conditional Probabilities; 2.5 Basic Combinatorics; 2.6 Bayes's Theorem; 2.7 Independence; 2.8 Discrete Random Variables; 2.9 Engineering Application-An Optical Communication System; Exercises
Section 2.1: Experiments, Sample Spaces, and EventsSection 2.2: Axioms of Probability; Section 2.3: Assigning Probabilities; Section 2.4: Joint and Conditional Probabilities; Section 2.5: Basic Combinatorics; Section 2.6: Bayes's Theorem; Section 2.7: Independence; Section 2.8: Discrete Random Variables; Miscellaneous Problems; MATLAB Exercises; Chapter 3: Random Variables, Distributions,and Density Functions; 3.1 The Cumulative Distribution Function; 3.2 The Probability Density Function; 3.3 The Gaussian Random Variable; 3.4 Other Important Random Variables; 3.4.1 Uniform Random Variable
3.4.2 Exponential Random Variable3.4.3 Laplace Random Variable; 3.4.4 Gamma Random Variable; 3.4.5 Erlang Random Variable; 3.4.6 Chi-Squared Random Variable; 3.4.7 Rayleigh Random Variable; 3.4.8 Rician Random Variable; 3.4.9 Cauchy Random Variable; 3.5 Conditional Distribution and Density Functions; 3.6 Engineering Application: Reliability and Failure Rates; Exercises; Section 3.1: The Cumulative Distribution Function; Section 3.2: The Probability Density Function; Section 3.3: The Gaussian Random Variable; Section 3.4: Other Important Random Variables
Section 3.5: Conditional Distribution and Density FunctionsSection 3.6: Reliability and Failure Rates; Miscellaneous Exercises; MATLAB Exercises; Chapter 4: Operations on a Single Random Variable; 4.1 Expected Value of a Random Variable; 4.2 Expected Values of Functions of Random Variables; 4.3 Moments; 4.4 Central Moments; 4.5 Conditional Expected Values; 4.6 Transformations of Random Variables; 4.6.1 Monotonically Increasing Functions; 4.6.2 Monotonically Decreasing Functions; 4.6.3 Nonmonotonic Functions; 4.7. Characteristic Functions; 4.8. Probability-Generating Functions
4.9 Moment-Generating Functions4.10 Evaluating Tail Probabilities; 4.11 Engineering Application-Scalar Quantization; 4.12 Engineering Application-Entropy and Source Coding; Exercises; Section 4.1: Expected Values of a Random Variable; Section 4.2: Expected Values of Functions of a Random Variable; Section 4.3: Moments; Section 4.4: Central Moments; Section 4.5: Conditional Expected Values; Section 4.6: Transformations of Random Variables; Section 4.7: Characteristic Functions; Section 4.8: Probability-Generating Functions; Section 4.9: Moment-Generating Functions
Section 4.10: Evaluating Tail Probabilities
Record Nr. UNINA-9910778937503321
Miller Scott L  
Waltham, Mass., : Elsevier, 2012
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Probability and random processes : with applications to signal processing and communications / / Scott L. Miller, Donald Childers
Probability and random processes : with applications to signal processing and communications / / Scott L. Miller, Donald Childers
Autore Miller Scott L
Edizione [Ed. 2.]
Pubbl/distr/stampa Waltham, Mass., : Elsevier, 2012
Descrizione fisica 1 online resource (625 p.)
Disciplina 621.382/20151
621.38220151
Altri autori (Persone) ChildersDonald G
Soggetto topico Signal processing - Mathematics
Probabilities
Stochastic processes
ISBN 1-283-41027-3
9786613410276
0-12-387013-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Front Cover; Probability and Random Processes: With Applications to Signal Processingand Communications; Copyright; Contents; Preface; Chapter 1: Introduction; 1.1 A Speech Recognition System; 1.2 A Radar System; 1.3 A Communication Network; Chapter 2: Introduction to Probability Theory; 2.1 Experiments, Sample Spaces, and Events; 2.2 Axioms of Probability; 2.3 Assigning Probabilities; 2.4 Joint and Conditional Probabilities; 2.5 Basic Combinatorics; 2.6 Bayes's Theorem; 2.7 Independence; 2.8 Discrete Random Variables; 2.9 Engineering Application-An Optical Communication System; Exercises
Section 2.1: Experiments, Sample Spaces, and EventsSection 2.2: Axioms of Probability; Section 2.3: Assigning Probabilities; Section 2.4: Joint and Conditional Probabilities; Section 2.5: Basic Combinatorics; Section 2.6: Bayes's Theorem; Section 2.7: Independence; Section 2.8: Discrete Random Variables; Miscellaneous Problems; MATLAB Exercises; Chapter 3: Random Variables, Distributions,and Density Functions; 3.1 The Cumulative Distribution Function; 3.2 The Probability Density Function; 3.3 The Gaussian Random Variable; 3.4 Other Important Random Variables; 3.4.1 Uniform Random Variable
3.4.2 Exponential Random Variable3.4.3 Laplace Random Variable; 3.4.4 Gamma Random Variable; 3.4.5 Erlang Random Variable; 3.4.6 Chi-Squared Random Variable; 3.4.7 Rayleigh Random Variable; 3.4.8 Rician Random Variable; 3.4.9 Cauchy Random Variable; 3.5 Conditional Distribution and Density Functions; 3.6 Engineering Application: Reliability and Failure Rates; Exercises; Section 3.1: The Cumulative Distribution Function; Section 3.2: The Probability Density Function; Section 3.3: The Gaussian Random Variable; Section 3.4: Other Important Random Variables
Section 3.5: Conditional Distribution and Density FunctionsSection 3.6: Reliability and Failure Rates; Miscellaneous Exercises; MATLAB Exercises; Chapter 4: Operations on a Single Random Variable; 4.1 Expected Value of a Random Variable; 4.2 Expected Values of Functions of Random Variables; 4.3 Moments; 4.4 Central Moments; 4.5 Conditional Expected Values; 4.6 Transformations of Random Variables; 4.6.1 Monotonically Increasing Functions; 4.6.2 Monotonically Decreasing Functions; 4.6.3 Nonmonotonic Functions; 4.7. Characteristic Functions; 4.8. Probability-Generating Functions
4.9 Moment-Generating Functions4.10 Evaluating Tail Probabilities; 4.11 Engineering Application-Scalar Quantization; 4.12 Engineering Application-Entropy and Source Coding; Exercises; Section 4.1: Expected Values of a Random Variable; Section 4.2: Expected Values of Functions of a Random Variable; Section 4.3: Moments; Section 4.4: Central Moments; Section 4.5: Conditional Expected Values; Section 4.6: Transformations of Random Variables; Section 4.7: Characteristic Functions; Section 4.8: Probability-Generating Functions; Section 4.9: Moment-Generating Functions
Section 4.10: Evaluating Tail Probabilities
Record Nr. UNINA-9910818170603321
Miller Scott L  
Waltham, Mass., : Elsevier, 2012
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Probability and random processes [[electronic resource] ] : with applications to signal processing and communications / / Scott L. Miller, Donald Childers
Probability and random processes [[electronic resource] ] : with applications to signal processing and communications / / Scott L. Miller, Donald Childers
Autore Miller Scott L
Pubbl/distr/stampa Amsterdam ; ; Boston, : Elsevier Academic Press, c2004
Descrizione fisica 1 online resource (551 p.)
Disciplina 621.382/2/0151
Altri autori (Persone) ChildersDonald G
Soggetto topico Signal processing - Mathematics
Probabilities
Stochastic processes
Soggetto genere / forma Electronic books.
ISBN 1-280-96126-0
9786610961269
0-08-047042-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Front Cover; Probability and Random Processes; Copyright Page; Contents; Preface; Chapter 1. Introduction; 1.1 A Speech Recognition System; 1.2 A Radar System; 1.3 A Communication Network; Chapter 2. Introduction to Probability Theory; 2.1 Experiments, Sample Spaces, and Events; 2.2 Axioms of Probability; 2.3 Assigning Probabilities; 2.4 Joint and Conditional Probabilities; 2.5 Bayes's Theorem; 2.6 Independence; 2.7 Discrete Random Variables; 2.8 Engineering Application: An Optical Communication System; Chapter 3. Random Variables, Distributions, and Density Functions
3.1 The Cumulative Distribution Function3.2 The Probability Density Function; 3.3 The Gaussian Random Variable; 3.4 Other Important Random Variables; 3.5 Conditional Distribution and Density Functions; 3.6 Engineering Application: Reliability and Failure Rates; Chapter 4. Operations on a Single Random Variable; 4.1 Expected Value of a Random Variable; 4.2 Expected Values of Functions of Random Variables; 4.3 Moments; 4.4 Central Moments; 4.5 Conditional Expected Values; 4.6 Transformations of Random Variables; 4.7 Characteristic Functions; 4.8 Probability Generating Functions
4.9 Moment Generating Functions4.10 Evaluating Tail Probabilities; 4.11 Engineering Application: Scalar Quantization; 4.12 Engineering Application: Entropy and Source Coding; Chapter 5. Pairs of Random Variables; 5.1 Joint Cumulative Distribution Functions; 5.2 Joint Probability Density Functions; 5.3 Joint Probability Mass Functions; 5.4 Conditional Distribution, Density, and Mass Functions; 5.5 Expected Values Involving Pairs of Random Variables; 5.6 Independent Random Variables; 5.7 Jointly Gaussian Random Variables; 5.8 Joint Characteristic and Related Functions
5.9 Transformations of Pairs of Random Variables5.10 Complex Random Variables; 5.11 Engineering Application: Mutual Information, Channel Capacity, and Channel Coding; Chapter 6. Multiple Random Variables; 6.1 Joint and Conditional PMFs, CDFs, and PDFs; 6.2 Expectations Involving Multiple Random Variables; 6.3 Gaussian Random Variables in Multiple Dimensions; 6.4 Transformations Involving Multiple Random Variables; 6.5 Engineering Application: Linear Prediction of Speech; Chapter 7. Random Sequences and Series; 7.1 Independent and Identically Distributed Random Variables
7.2 Convergence Modes of Random Sequences7.3 The Law of Large Numbers; 7.4 The Central Limit Theorem; 7.5 Confidence Intervals; 7.6 Random Sums of Random Variables; 7.7 Engineering Application: A Radar System; Chapter 8. Random Processes; 8.1 Definition and Classification of Processes; 8.2 Mathematical Tools for Studying Random Processes; 8.3 Stationary and Ergodic Random Processes; 8.4 Properties of the Autocorrelation Function; 8.5 Gaussian Random Processes; 8.6 Poisson Processes; 8.7 Engineering Application: Shot Noise in a p-n Junction Diode; Chapter 9. Markov Processes
9.1 Definition and Examples of Markov Processes
Record Nr. UNINA-9910458699103321
Miller Scott L  
Amsterdam ; ; Boston, : Elsevier Academic Press, c2004
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Probability and random processes [[electronic resource] ] : with applications to signal processing and communications / / Scott L. Miller, Donald Childers
Probability and random processes [[electronic resource] ] : with applications to signal processing and communications / / Scott L. Miller, Donald Childers
Autore Miller Scott L
Pubbl/distr/stampa Amsterdam ; ; Boston, : Elsevier Academic Press, c2004
Descrizione fisica 1 online resource (551 p.)
Disciplina 621.382/2/0151
Altri autori (Persone) ChildersDonald G
Soggetto topico Signal processing - Mathematics
Probabilities
Stochastic processes
ISBN 1-280-96126-0
9786610961269
0-08-047042-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Front Cover; Probability and Random Processes; Copyright Page; Contents; Preface; Chapter 1. Introduction; 1.1 A Speech Recognition System; 1.2 A Radar System; 1.3 A Communication Network; Chapter 2. Introduction to Probability Theory; 2.1 Experiments, Sample Spaces, and Events; 2.2 Axioms of Probability; 2.3 Assigning Probabilities; 2.4 Joint and Conditional Probabilities; 2.5 Bayes's Theorem; 2.6 Independence; 2.7 Discrete Random Variables; 2.8 Engineering Application: An Optical Communication System; Chapter 3. Random Variables, Distributions, and Density Functions
3.1 The Cumulative Distribution Function3.2 The Probability Density Function; 3.3 The Gaussian Random Variable; 3.4 Other Important Random Variables; 3.5 Conditional Distribution and Density Functions; 3.6 Engineering Application: Reliability and Failure Rates; Chapter 4. Operations on a Single Random Variable; 4.1 Expected Value of a Random Variable; 4.2 Expected Values of Functions of Random Variables; 4.3 Moments; 4.4 Central Moments; 4.5 Conditional Expected Values; 4.6 Transformations of Random Variables; 4.7 Characteristic Functions; 4.8 Probability Generating Functions
4.9 Moment Generating Functions4.10 Evaluating Tail Probabilities; 4.11 Engineering Application: Scalar Quantization; 4.12 Engineering Application: Entropy and Source Coding; Chapter 5. Pairs of Random Variables; 5.1 Joint Cumulative Distribution Functions; 5.2 Joint Probability Density Functions; 5.3 Joint Probability Mass Functions; 5.4 Conditional Distribution, Density, and Mass Functions; 5.5 Expected Values Involving Pairs of Random Variables; 5.6 Independent Random Variables; 5.7 Jointly Gaussian Random Variables; 5.8 Joint Characteristic and Related Functions
5.9 Transformations of Pairs of Random Variables5.10 Complex Random Variables; 5.11 Engineering Application: Mutual Information, Channel Capacity, and Channel Coding; Chapter 6. Multiple Random Variables; 6.1 Joint and Conditional PMFs, CDFs, and PDFs; 6.2 Expectations Involving Multiple Random Variables; 6.3 Gaussian Random Variables in Multiple Dimensions; 6.4 Transformations Involving Multiple Random Variables; 6.5 Engineering Application: Linear Prediction of Speech; Chapter 7. Random Sequences and Series; 7.1 Independent and Identically Distributed Random Variables
7.2 Convergence Modes of Random Sequences7.3 The Law of Large Numbers; 7.4 The Central Limit Theorem; 7.5 Confidence Intervals; 7.6 Random Sums of Random Variables; 7.7 Engineering Application: A Radar System; Chapter 8. Random Processes; 8.1 Definition and Classification of Processes; 8.2 Mathematical Tools for Studying Random Processes; 8.3 Stationary and Ergodic Random Processes; 8.4 Properties of the Autocorrelation Function; 8.5 Gaussian Random Processes; 8.6 Poisson Processes; 8.7 Engineering Application: Shot Noise in a p-n Junction Diode; Chapter 9. Markov Processes
9.1 Definition and Examples of Markov Processes
Record Nr. UNINA-9910784646003321
Miller Scott L  
Amsterdam ; ; Boston, : Elsevier Academic Press, c2004
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Probability and random processes : with applications to signal processing and communications / / Scott L. Miller, Donald Childers
Probability and random processes : with applications to signal processing and communications / / Scott L. Miller, Donald Childers
Autore Miller Scott L
Edizione [1st ed.]
Pubbl/distr/stampa Amsterdam ; ; Boston, : Elsevier Academic Press, c2004
Descrizione fisica 1 online resource (551 p.)
Disciplina 621.382/2/0151
Altri autori (Persone) ChildersDonald G
Soggetto topico Signal processing - Mathematics
Probabilities
Stochastic processes
ISBN 1-280-96126-0
9786610961269
0-08-047042-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Front Cover; Probability and Random Processes; Copyright Page; Contents; Preface; Chapter 1. Introduction; 1.1 A Speech Recognition System; 1.2 A Radar System; 1.3 A Communication Network; Chapter 2. Introduction to Probability Theory; 2.1 Experiments, Sample Spaces, and Events; 2.2 Axioms of Probability; 2.3 Assigning Probabilities; 2.4 Joint and Conditional Probabilities; 2.5 Bayes's Theorem; 2.6 Independence; 2.7 Discrete Random Variables; 2.8 Engineering Application: An Optical Communication System; Chapter 3. Random Variables, Distributions, and Density Functions
3.1 The Cumulative Distribution Function3.2 The Probability Density Function; 3.3 The Gaussian Random Variable; 3.4 Other Important Random Variables; 3.5 Conditional Distribution and Density Functions; 3.6 Engineering Application: Reliability and Failure Rates; Chapter 4. Operations on a Single Random Variable; 4.1 Expected Value of a Random Variable; 4.2 Expected Values of Functions of Random Variables; 4.3 Moments; 4.4 Central Moments; 4.5 Conditional Expected Values; 4.6 Transformations of Random Variables; 4.7 Characteristic Functions; 4.8 Probability Generating Functions
4.9 Moment Generating Functions4.10 Evaluating Tail Probabilities; 4.11 Engineering Application: Scalar Quantization; 4.12 Engineering Application: Entropy and Source Coding; Chapter 5. Pairs of Random Variables; 5.1 Joint Cumulative Distribution Functions; 5.2 Joint Probability Density Functions; 5.3 Joint Probability Mass Functions; 5.4 Conditional Distribution, Density, and Mass Functions; 5.5 Expected Values Involving Pairs of Random Variables; 5.6 Independent Random Variables; 5.7 Jointly Gaussian Random Variables; 5.8 Joint Characteristic and Related Functions
5.9 Transformations of Pairs of Random Variables5.10 Complex Random Variables; 5.11 Engineering Application: Mutual Information, Channel Capacity, and Channel Coding; Chapter 6. Multiple Random Variables; 6.1 Joint and Conditional PMFs, CDFs, and PDFs; 6.2 Expectations Involving Multiple Random Variables; 6.3 Gaussian Random Variables in Multiple Dimensions; 6.4 Transformations Involving Multiple Random Variables; 6.5 Engineering Application: Linear Prediction of Speech; Chapter 7. Random Sequences and Series; 7.1 Independent and Identically Distributed Random Variables
7.2 Convergence Modes of Random Sequences7.3 The Law of Large Numbers; 7.4 The Central Limit Theorem; 7.5 Confidence Intervals; 7.6 Random Sums of Random Variables; 7.7 Engineering Application: A Radar System; Chapter 8. Random Processes; 8.1 Definition and Classification of Processes; 8.2 Mathematical Tools for Studying Random Processes; 8.3 Stationary and Ergodic Random Processes; 8.4 Properties of the Autocorrelation Function; 8.5 Gaussian Random Processes; 8.6 Poisson Processes; 8.7 Engineering Application: Shot Noise in a p-n Junction Diode; Chapter 9. Markov Processes
9.1 Definition and Examples of Markov Processes
Record Nr. UNINA-9910810778103321
Miller Scott L  
Amsterdam ; ; Boston, : Elsevier Academic Press, c2004
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui