QuickBooks 2009 All in One For Dummies or Digital Signal Processing

QuickBooks 2009 All-in-One For Dummies

Author: Stephen L Nelson CPA MBA MS

QuickBooks accounting software is the favorite financial management and accounting software for small businesses, but it does take a little getting used to. QuickBooks 2009 All-in-One For Dummies is the QuickBooks reference guide that gets you through the learning curve in a hurry. Eight handy minibooks cover:

• An Accounting Primer
  
• Getting Ready to Use QuickBooks
  
• Bookkeeping Chores
  
• Accounting Chores
  
• Financial Management
  
• Business Plans
  
• Care and Maintenance
  
• Additional Business Resources
  

QuickBooks 2009 All-in-One For Dummies is written for the Premier version, but you’ll find the information works for the other versions too. It’s easy to find what you need to know:

• Book I covers all the basic accounting stuff for those who don’t know a credit from a debit
  
• Learn to set up the program, load files, and customize QuickBooks in Book II
  
• In Book III you’ll see how to invoice customers, pay vendors, track inventory, and more
  
• Take on activity-based costing, preparing a budget, and job costing in Book IV
  
• Book V gets into cool stuff like ratio analysis, EVA, and capital budgeting
  
• Find out in Book VI how to write the business plan you need
  
• Book VII shows you how to manage maintenance for QuickBooks
  
• Book VIII covers additional resources, an Excel primer, accounting terms, and more
  

Before you know it, you’ll be managing your business finances like a pro with QuickBooks 2009!

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Digital Signal Processing: A Computer Science Perspective, Vol. 1

Author: Jonathan Y Stein

Get a working knowledge of digital signal processing for computer science applications

The field of digital signal processing (DSP) is rapidly exploding, yet most books on the subject do not reflect the real world of algorithm development, coding for applications, and software engineering. This important new work fills the gap in the field, providing computer professionals with a comprehensive introduction to those aspects of DSP essential for working on today's cutting-edge applications in speech compression and recognition and modem design. The author walks readers through a variety of advanced topics, clearly demonstrating how even such areas as spectral analysis, adaptive and nonlinear filtering, or communications and speech signal processing can be made readily accessible through clear presentations and a practical hands-on approach. In a light, reader-friendly style, Digital Signal Processing: A Computer Science Perspective provides:
* A unified treatment of the theory and practice of DSP at a level sufficient for exploring the contemporary professional literature
* Thorough coverage of the fundamental algorithms and structures needed for designing and coding DSP applications in a high level language
* Detailed explanations of the principles of digital signal processors that will allow readers to investigate assembly languages of specific processors
* A review of special algorithms used in several important areas of DSP, including speech compression/recognition and digital communications
* More than 200 illustrations as well as an appendix containing the essential mathematical background

Choice

This...book offers a contemporary and comprehensive treatment of DSP.

Choice

This...book offers a contemporary and comprehensive treatment of DSP.

Booknews

While Stein was working for a high-tech company in Tel Aviv, he had no trouble finding experts in digital signal processing, but when he relocated to New York, he could find none. He discovered that it was not taught at all in the US at the undergraduate level, and at the graduate level only for electrical engineers. He developed and taught (Polytechnic U.) an undergraduate course for computer science majors, based on exactly the requirements he needed for his company. From that course emerged this textbook. He explains the theory and practice, the fundamental algorithms and structures used in computation, the principles of digital signal processors and how they differ from conventional ones, and some special areas of current research and develop such as speech compression and recognition and digital communications. Annotation c. Book News, Inc., Portland, OR (booknews.com)

Table of Contents:

	Preface	xv
1	Introductions	1
1.1	Prehistory of DSP	2
1.2	Some Applications of Signal Processing	4
1.3	Analog Signal Processing	7
1.4	Digital Signal Processing	10
Part I	Signal Analysis
2	Signals	15
2.1	Signal Defined	15
2.2	The Simplest Signals	20
2.3	Characteristics of Signals	30
2.4	Signal Arithmetic	33
2.5	The Vector Space of All Possible Signals	40
2.6	Time and Frequency Domains	44
2.7	Analog and Digital Domains	47
2.8	Sampling	49
2.9	Digitization	57
2.10	Antialiasing and Reconstruction Filters	62
2.11	Practical Analog to Digital Conversion	64
3	The Spectrum of Periodic Signals	71
3.1	Newton's Discovery	72
3.2	Frequency Components	74
3.3	Fourier's Discovery	77
3.4	Representation by Fourier Series	80
3.5	Gibbs Phenomenon	86
3.6	Complex FS and Negative Frequencies	90
3.7	Properties of Fourier Series	94
3.8	The Fourier Series of Rectangular Wave	96
4	The Frequency Domain	103
4.1	From Fourier Series to Fourier Transform	103
4.2	Fourier Transform Examples	110
4.3	FT Properties	113
4.4	The Uncertainty Theorem	117
4.5	Power Spectrum	122
4.6	Short Time Fourier Transform (STFT)	126
4.7	The Discrete Fourier Transform (DFT)	132
4.8	DFT Properties	135
4.9	Further Insights into the DFT	141
4.10	The z Transform	143
4.11	More on the z Transform	151
4.12	The Other Meaning of Frequency	155
5	Noise	161
5.1	Unpredictable Signals	162
5.2	A Naive View of Noise	164
5.3	Noise Reduction by Averaging	171
5.4	Pseudorandom Signals	174
5.5	Chaotic Signals	180
5.6	Stochastic Signals	192
5.7	Spectrum of Random Signals	198
5.8	Stochastic Approximation Methods	202
5.9	Probabilistic Algorithms	203
Part II	Signal Processing Systems
6	Systems	207
6.1	System Defined	208
6.2	The Simplest Systems	209
6.3	The Simplest Systems with Memory	213
6.4	Characteristics of Systems	221
6.5	Filters	226
6.6	Moving Averages in the Time Domain	228
6.7	Moving Averages in the Frequency Domain	231
6.8	Why Convolve?	237
6.9	Purely Recursive Systems	241
6.10	Difference Equations	245
6.11	The Sinusoid's Equation	249
6.12	System Identification--The Easy Case	252
6.13	System Identification--The Hard Case	259
6.14	System Identification in the z Domain	265
7	Filters	271
7.1	Filter Specification	272
7.2	Phase and Group Delay	275
7.3	Special Filters	279
7.4	Feedback	289
7.5	The ARMA Transfer Function	293
7.6	Pole-Zero Plots	298
7.7	Classical Filter Design	303
7.8	Digital Filter Design	309
7.9	Spatial Filtering	315
8	Nonfilters	321
8.1	Nonlinearities	322
8.2	Clippers and Slicers	324
8.3	Median Filters	326
8.4	Multilayer Nonlinear Systems	329
8.5	Mixers	332
8.6	Phase-Locked Loops	338
8.7	Time Warping	343
9	Correlation	349
9.1	Signal Comparison and Detection	350
9.2	Crosscorrelation and Autocorrelation	354
9.3	The Wiener-Khintchine Theorem	357
9.4	The Frequency Domain Signal Detector	359
9.5	Correlation and Convolution	361
9.6	Application to Radar	362
9.7	The Wiener Filter	365
9.8	Correlation and Prediction	369
9.9	Linear Predictive Coding	371
9.10	The Levinson-Durbin Recursion	376
9.11	Line Spectral Pairs	383
9.12	Higher-Order Signal Processing	386
10	Adaptation	393
10.1	Adaptive Noise Cancellation	394
10.2	Adaptive Echo Cancellation	400
10.3	Adaptive Equalization	404
10.4	Weight Space	408
10.5	The LMS Algorithm	413
10.6	Other Adaptive Algorithms	420
11	Biological Signal Processing	427
11.1	Weber's Discovery	428
11.2	The Birth of Psychophysics	430
11.3	Speech Production	435
11.4	Speech Perception	439
11.5	Brains and Neurons	442
11.6	The Essential Neural Network	446
11.7	The Simplest Model Neuron	448
11.8	Man vs. Machine	452
Part III	Architectures and Algorithms
12	Graphical Techniques	461
12.1	Graph Theory	462
12.2	DSP Flow Graphs	467
12.3	DSP Graph Manipulation	476
12.4	RAX Externals	481
12.5	RAX Internals	487
13	Spectral Analysis	495
13.1	Zero Crossings	496
13.2	Bank of Filters	498
13.3	The Periodogram	502
13.4	Windows	506
13.5	Finding a Sinusoid in Noise	512
13.6	Finding Sinusoids in Noise	515
13.7	IIR Methods	520
13.8	Walsh Functions	523
13.9	Wavelets	526
14	The Fast Fourier Transform	531
14.1	Complexity of the DFT	532
14.2	Two Preliminary Examples	536
14.3	Derivation of the DIT FFT	539
14.4	Other Common FFT Algorithms	546
14.5	The Matrix Interpretation of the FFT	552
14.6	Practical Matters	554
14.7	Special Cases	558
14.8	Goertzel's Algorithm	561
14.9	FIFO Fourier Transform	565
15	Digital Filter Implementation	569
15.1	Computation of Convolutions	570
15.2	FIR Filtering in the Frequency Domain	573
15.3	FIR Structures	579
15.4	Polyphase Filters	584
15.5	Fixed Point Computation	590
15.6	IIR Structures	595
15.7	FIR vs. IIR	602
16	Function Evaluation Algorithms	605
16.1	Sine and Cosine Generation	606
16.2	Arctangent	609
16.3	Logarithm	610
16.4	Square Root and Pythagorean Addition	611
16.5	CORDIC Algorithms	613
17	Digital Signal Processors	619
17.1	Multiply-and-Accumulate (MAC)	620
17.2	Memory Architecture	623
17.3	Pipelines	627
17.5	Interrupts, Ports	631
17.5	Fixed and Floating Point	633
17.6	A Real-Time Filter	635
17.7	DSP Programming Projects	639
17.8	DSP Development Teams	641
Part IV	Applications
18	Communications Signal Processing	647
18.1	History of Communications	648
18.2	Analog Modulation Types	652
18.3	AM	655
18.4	FM and PM	659
18.5	Data Communications	664
18.6	Information Theory	666
18.7	Communications Theory	670
18.8	Channel Capacity	674
18.9	Error Correcting Codes	680
18.10	Block Codes	683
18.11	Convolutional Codes	690
18.12	PAM and FSK	698
18.13	PSK	704
18.14	Modem Spectra	708
18.15	Timing Recovery	710
18.16	Equalization	714
18.17	QAM	716
18.18	QAM Slicers	720
18.19	Trellis Coding	723
18.20	Telephone-Grade Modems	729
18.21	Beyond the Shannon Limit	733
19	Speech Signal Processing	739
19.1	LPC Speech Synthesis	740
19.2	LPC Speech Analysis	742
19.3	Cepstrum	744
19.4	Other Features	747
19.5	Pitch Tracking and Voicing Determination	750
19.6	Speech Compression	753
19.7	PCM	757
19.8	DPCM, DM, and ADPCM	760
19.9	Vector Quantization	765
19.10	SBC	768
19.11	LPC Speech Compression	770
19.12	CELP Coders	771
19.13	Telephone-Grade Speech Coding	775
A	Whirlwind Exposition of Mathematics	781
A.1	Numbers	781
A.2	Integers	782
A.3	Real Numbers	784
A.4	Complex Numbers	785
A.5	Abstract Algebra	788
A.6	Functions and Polynomials	791
A.7	Elementary Functions	793
A.8	Trigonometric (and Similar) Functions	795
A.9	Analysis	800
A.10	Differential Equations	803
A.11	The Dirac Delta	808
A.12	Approximation by Polynomials	809
A.13	Probability Theory	815
A.14	Linear Algebra	819
A.15	Matrices	821
A.16	Solution of Linear Algebraic Equations	826
	Bibliography	829
	Index	849