Inflation Prediction

Target Date

Inflation Data (1960–2023)

Year	Inflation (%)
1960	1.779877847
1961	1.695212939
1962	3.632214971
1963	2.946161357
1964	13.35526115
1965	9.474758592
1966	10.80184835
1967	13.06220248
1968	3.237412426
1969	-0.58413661
1970	5.09226162
1971	3.079938684
1972	6.442097462
1973	16.94081598
1974	28.59873408
1975	5.748430298
1976	-7.633947634
1977	8.307470092
1978	2.523048757
1979	6.275683368
1980	11.34607348
1981	13.1125469
1982	7.890742794
1983	11.8680813
1984	8.318907119
1985	5.556424232
1986	8.729720727
1987	8.801125813
1988	9.383471862
1989	7.074280029
1990	8.971232503
1991	13.87024618
1992	11.78781704
1993	6.326890488
1994	10.24793556
1995	10.22488616
1996	8.977152338
1997	7.164252115
1998	13.23083898
1999	4.66982038
2000	4.00943591
2001	3.779293122
2002	4.297152039
2003	3.805858995
2004	3.767251735
2005	4.24634362
2006	5.796523376
2007	6.372881356
2008	8.349267049
2009	10.88235294
2010	11.98938992
2011	8.911793365
2012	9.478996914
2013	10.01787847
2014	6.665656719
2015	4.906973441
2016	4.948216341
2017	3.328173375
2018	3.938826467
2019	3.729505735
2020	6.623436776
2021	5.131407472
2022	6.699034141
2023	5.649143189

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Q-function in BER vs SNR Calculation (with Simulation)

Q-function in BER vs. SNR Calculation In digital communications and signal processing, the Q-function plays a significant role in predicting system reliability. It allows engineers to quantify the probability that Gaussian noise will exceed a specific threshold, causing a bit error. What is the Q-function? The Q-function is a mathematical function representing the tail probability of the standard normal (Gaussian) distribution. It is the complementary cumulative distribution function (CCDF) of a standard Gaussian distribution. Q(x) = (1 / √(2π)) ∫ₓ∞ e^(-t² / 2) dt Q-Function Interactive Simulator Move the slider to see how the "Tail Probability" (the area in red) changes. This area represents the Probability of Error (BER) . Threshold Distance ( x ) — (Simulates Increasing SNR) x = 1.0 Q(x) = 0.1587 ...

Design of CMOS Flip-Flops (SR, D, JK)

Design of CMOS Flip-Flops (SR, D, JK) A flip-flop or latch is a circuit with two stable states, used to store state information. It is the basic storage element in sequential logic and a fundamental building block in digital electronics systems, including computers and communication devices. Flip-flops and latches act as data storage elements for states, pulse counting, and synchronization of variably-timed input signals to a reference clock. Flip-flops can be transparent/opaque (latches) or clocked (synchronous, edge-triggered). Latches are level-sensitive, while flip-flops are edge-sensitive. In sequential logic, the output depends on current inputs and previous states. Fig.1 shows a sequential circuit combining a combinational block and a memory element. ...

Pulse Width Modulation (PWM)

Pulse-width modulation (PWM), or pulse-duration modulation (PDM), is a method of controlling the average power delivered by an electrical signal. Fig: An example of PWM in an idealized inductor driven by a blue line voltage source modulated as a series of sawtooth pulses, resulting in a red line current in the inductor. Generating a PWM Signal The simplest way to generate a PWM signal is the intersection method, which requires only a sawtooth or a triangle waveform (easily generated using a simple oscillator) and a comparator. When the value of the reference signal is more than the modulation waveform, the PWM signal (magenta) is in the high state; otherwise, it is in the low state. Duty cycle A low duty cycle equates to low power because the power is off for most of the time; the word duty cycle reflects the ratio of "on" time to the regular interval or "period" of time. The duty cycle is measured in percent, with 100% representing full o...

BER vs SNR for M-ary QAM, M-ary PSK, QPSK, BPSK, ...(MATLAB Code + Simulator)

Bit Error Rate (BER) & SNR Guide Analyze communication system performance with our interactive simulators and MATLAB tools. 📘 Theory 🧮 Simulators 💻 MATLAB Code 📚 Resources BER Definition SNR Formula BER Calculator MATLAB Comparison 📂 Explore M-ary QAM, PSK, and QPSK Topics ▼ 🧮 Constellation Simulator: M-ary QAM 🧮 Constellation Simulator: M-ary PSK 🧮 BER calculation for ASK, FSK, and PSK 🧮 Approaches to BER vs SNR What is Bit Error Rate (BER)? The BER indicates how many corrupted bits are received compared to the total number of bits sent. It is the primary figure of merit f...

FFT Butterfly Method Explained (with Example of 4-point DFT)

FFT Using Butterfly Method Given: x[n] = {0, 1, 2, 3} Step 1: Split into Even & Odd Even indices: x e = {0, 2} Odd indices: x o = {1, 3} Step 2: 2-point DFT For any {a, b}: DFT = {a + b, a - b} Even Part: E = {0+2, 0-2} = {2, -2} Odd Part: O = {1+3, 1-3} = {4, -2} Step 3: Combine Using Butterfly X[k] = E[k] + W k O[k] X[k + N/2] = E[k] - W k O[k] For N = 4: W 0 = 1 W 1 = -j Final Calculations X[0] = 2 + 4 = 6 X[2] = 2 - 4 = -2 X[1] = -2 + (-j)(-2) = -2 + 2j X[3] = -2 - (-j)(-2) = -2 - 2j Final Answer: X[k] = {6, -2 + 2j, -2, -2 - 2j} Try Interactive Online Simulations Interactive FFT Online Simulator (For understanding Fundamentals) Interactive FFT Online Simulator (Analyze .CSV, .MP3, .MP4, etc. Further Reading Fourier Transform OFDM Return to Fourier Transform Main Page →

Frequency Shift Keying (FSK) Modulation & Demodulation (with Simulation)

Frequency Shift Keying (FSK) Theoretical Foundations: Frequency Shift Keying (FSK) is a discrete frequency modulation scheme wherein the digital information is encoded via instantaneous shifts in the carrier signal's frequency. The fundamental implementation is Binary FSK (BFSK), which maps binary data onto two distinct, discrete spectral states. A binary '1' (the "mark" state) is represented by a carrier frequency \( f_1 \), while a binary '0' (the "space" state) corresponds to frequency \( f_2 \). Each symbol is sustained for a bit interval denoted by \( T_b \). FSK Transmitter Characterization: The mathematical model for the modulated BFSK output \( s(t) \) is defined as: \[ s(t) = \begin{cases} A_c \cos(2\pi f_1 t), & \text{for } m = 1 \\ A_c \cos(2\pi f_2 t), & \text{for } m = 0 \end{cases} \] ...

AM Modulation Online Simulator

Amplitude Modulation Simulator s AM (t) = A c [1 + k a m(t)] cos(ω c t) where, ω = 2πf & k a = Amplitude Sensitivity Modulation index, μ = k a A m Message Frequency (fm): Carrier Frequency (fc): Carrier Amplitude (Ac): Modulation Index (m = Am / Ac):

Online Simulator for ASK, FSK, and PSK

Interactive Digital Signal Processing (DSP) Tutorial and Simulator for ASK, FSK, and BPSK modulation techniques. Try our new Digital Signal Processing Simulator! • Interactive ASK, FSK, and BPSK tools updated for 2025. Start Now Digital Modulation Visualizer: ASK, FSK, & BPSK Simulator Learn and visualize binary modulation techniques (ASK, FSK, BPSK) in real-time with adjustable carrier and sampling parameters. Perfect for DSP students and engineers. 📡 ASK Simulator 📶 FSK Simulator 🎚️ BPSK Simulator 📚 More Topics ASK Modulator FSK Modulator BPSK Modulator More Topics 1. ASK (Amplitude Shift Keying) Simulat...

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